diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index ea89874..01e31b8 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -15,7 +15,7 @@ jobs:
         with:
           python-version: "3.12"
       - name: Install (with dev and type-check extras)
-        run: uv pip install -e ".[dev,typecheck]"
+        run: uv pip install --prerelease=allow -e ".[dev,typecheck,async]"
       - name: Type check
         run: uv run --no-sync mypy
 
@@ -32,7 +32,7 @@ jobs:
         with:
           python-version: ${{ matrix.python-version }}
       - name: Install (with dev extras)
-        run: uv pip install -e ".[dev,ingest,langchain,dspy,llamaindex,haystack]"
+        run: uv pip install --prerelease=allow -e ".[dev,ingest,langchain,dspy,llamaindex,haystack,async]"
       - name: Lint
         run: uv run --no-sync ruff check src benchmarks
       - name: Test
diff --git a/dashboard/.gitignore b/dashboard/.gitignore
deleted file mode 100644
index 9407060..0000000
--- a/dashboard/.gitignore
+++ /dev/null
@@ -1,6 +0,0 @@
-node_modules/
-.next/
-out/
-next-env.d.ts
-*.tsbuildinfo
-.DS_Store
diff --git a/dashboard/README.md b/dashboard/README.md
deleted file mode 100644
index d8653d0..0000000
--- a/dashboard/README.md
+++ /dev/null
@@ -1,117 +0,0 @@
-# dynavec observability dashboard
-
-A Langfuse-style observability UI for dynavec, in the project's brand theme. It
-shows **real** query telemetry — latency percentiles, cache hit-rate, query
-volume, and a filterable traces table with per-trace drill-down.
-
-![dynavec observability dashboard](https://raw.githubusercontent.com/codeforstartups/dynavec/development/docs/assets/dashboard.png)
-
----
-
-## How it fits together
-
-Two pieces, split by language boundary:
-
-```
-your app ──▶ Dynavec(..., telemetry=recorder)      # records real events (Python)
-                     │
-                     ▼
-        dynavec.dashboard.serve(recorder)           # JSON API  (Python, stdlib)
-          GET /api/metrics · /api/traces · /api/trace/{id}
-                     │  (fetch)
-                     ▼
-        dashboard/  (Next.js + Tailwind + Recharts) # this app (TypeScript)
-```
-
-- **Data source:** `src/dynavec/telemetry.py` captures a `TelemetryEvent` for
-  every real `search`; `src/dynavec/dashboard.py::serve()` exposes it as JSON.
-- **This app** reads that API via `NEXT_PUBLIC_DYNAVEC_API` and renders it. With
-  no API configured it falls back to sample data (so `npm run dev` works alone).
-
-## Run it
-
-```bash
-# 1) produce real telemetry + serve the API (no AWS needed)
-python examples/dashboard_demo.py            # API on http://127.0.0.1:8779
-
-# 2) run the dashboard against it
-cd dashboard
-npm install
-NEXT_PUBLIC_DYNAVEC_API=http://127.0.0.1:8779 npm run dev   # http://localhost:3000
-
-# build a static export (deployable to any static host / GitHub Pages)
-npm run build        # -> dashboard/out/
-```
-
-## File map
-
-| Path | Role |
-|------|------|
-| `app/page.tsx` | top-level state (window, filters, polling) + layout |
-| `components/TopBar.tsx` | brand, time-range, auto-refresh, live/sample badge |
-| `components/Sidebar.tsx` | navigation / information architecture |
-| `components/Kpis.tsx` | KPI cards (QPM, p95, cache-hit, avg results, errors) |
-| `components/VolumeChart.tsx` | Recharts query-volume histogram |
-| `components/LatencyChart.tsx` | p50/p95/p99 percentile bars |
-| `components/TracesTable.tsx` | filterable traces table |
-| `components/TraceDrawer.tsx` | per-trace detail drawer |
-| `lib/types.ts` | `Metrics` / `TraceEvent` types (mirror the Python API) |
-| `lib/api.ts` | data fetching + sample fallback |
-| `lib/mock.ts` | sample-data generator for standalone dev |
-| `tailwind.config.ts` | brand tokens (coral `#e8623b`, warm ink, fonts) |
-
----
-
-## What's done ✅
-
-- [x] Telemetry capture on the real `search` path (opt-in `telemetry=recorder`)
-- [x] JSON API: `/api/metrics`, `/api/traces`, `/api/trace/{id}`
-- [x] Next.js app: KPIs, volume histogram, latency percentiles, traces table + drawer
-- [x] Brand theme, time-range selector, auto-refresh, sample-data fallback
-
-## Remaining work — pick a task 🙌
-
-Each item is a self-contained contribution. Comment on the linked issue to claim
-it. Parent: **[dashboard epic #122](https://github.com/codeforstartups/dynavec/issues/122)**.
-
-### 1. Instrument `upsert` and `graph_search` (backend)
-Only `search` records telemetry today.
-- [ ] Record `TelemetryEvent(op="upsert", ...)` in `Dynavec.upsert` (count, latency)
-- [ ] Record `op="graph_search"` in `Dynavec.graph_search`
-- [ ] Tests in `tests/test_telemetry.py` / `tests/test_client_inmemory.py`
-
-### 2. Evaluation panel — recall@k / faithfulness ([#134](https://github.com/codeforstartups/dynavec/issues/134), [#135](https://github.com/codeforstartups/dynavec/issues/135))
-- [ ] Backend: an eval runner that scores a labeled set (recall@k, MRR, nDCG) and stores results; a pluggable LLM-judge for faithfulness/answer-relevance
-- [ ] API: `GET /api/eval/summary`, `GET /api/eval/runs`
-- [ ] UI: new `components/EvalPanel.tsx` + a "Scores" route/section (wire the sidebar item, currently `soon`); trend charts with Recharts
-
-### 3. Resources panel — buckets / indexes / namespaces ([#128](https://github.com/codeforstartups/dynavec/issues/128), [#129](https://github.com/codeforstartups/dynavec/issues/129))
-- [ ] Backend: `GET /api/resources` (describe S3 vector bucket + index dim/metric, DynamoDB table status) and `GET /api/namespaces` (per-namespace vector/doc counts)
-- [ ] UI: `components/ResourcesPanel.tsx`, `components/NamespaceExplorer.tsx`; wire the two `soon` sidebar items
-
-### 4. Cost panel ([#130](https://github.com/codeforstartups/dynavec/issues/130))
-- [ ] Backend: `GET /api/cost` reusing `benchmarks/cost_model` with live resource sizes + query volume
-- [ ] UI: `components/CostPanel.tsx` (breakdown + Recharts)
-
-### 5. Per-query stage waterfall
-The drawer shows total latency only.
-- [ ] Backend: capture per-stage timings (embed → query → hydrate → rerank) on the event
-- [ ] UI: a small waterfall in `TraceDrawer.tsx`
-
-### 6. Deploy to GitHub Pages
-- [ ] `.github/workflows/dashboard-pages.yml` that builds `dashboard/` with
-      `NEXT_PUBLIC_BASE_PATH=/dynavec/dashboard` and publishes `out/`
-      *(note: touches a workflow file — needs a maintainer with `workflow` scope to merge)*
-
-### 7. Polish
-- [ ] Dark mode toggle (theme parity with the landing page)
-- [ ] Sessions / Users grouping views
-- [ ] Column config + saved views
-- [ ] Component tests (Vitest / Testing Library)
-
-## Conventions
-
-- Keep the brand tokens in `tailwind.config.ts` in sync with the site's `styles.css`.
-- New API fields go in **both** `src/dynavec/telemetry.py` and `lib/types.ts`.
-- Charts use **Recharts**; keep them theme-colored (coral `#e8623b`, green `#2f7d5b`).
-- Run `npm run build` before opening a PR; keep `node_modules/`, `.next/`, `out/` out of git.
diff --git a/dashboard/app/globals.css b/dashboard/app/globals.css
deleted file mode 100644
index 9c599b8..0000000
--- a/dashboard/app/globals.css
+++ /dev/null
@@ -1,79 +0,0 @@
-@import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&family=JetBrains+Mono:wght@400;500;700&display=swap');
-@tailwind base;
-@tailwind components;
-@tailwind utilities;
-
-/* --- Light: the landing-site palette (styles.css) --- */
-:root {
-  color-scheme: light;
-
-  --bg: #fbfaf8;          /* warm paper */
-  --surface: #ffffff;
-  --ink: #14110f;         /* warm near-black */
-  --muted: #6f6862;
-  --faint: #a99f97;
-  --line: #ece6df;
-  --accent: #e8623b;      /* coral */
-  --accent-ink: #b8472a;  /* darker coral for text/hover on light */
-  --accent-soft: #fdeee8; /* light coral wash */
-  --ok: #2f7d5b;
-  --err: #b8472a;
-
-  --track: #f0ece6;       /* meter/track fill */
-  --thead: #faf6f1;       /* table header wash */
-  --shadow: rgba(20, 17, 15, .07);
-  --scroll-thumb: #e0d9d1;
-  --tip-bg: #ffffff;      /* recharts tooltip */
-  --tip-line: #ece6df;
-
-  /* op badges */
-  --op-search-bg: #eef3ff; --op-search-fg: #3b5bdb; --op-search-line: #dbe3ff;
-  --op-graph-bg: #f3eeff;  --op-graph-fg: #7048e8;  --op-graph-line: #e5dbff;
-  --op-upsert-bg: #eafaf1; --op-upsert-fg: #2f7d5b; --op-upsert-line: #d3f0e0;
-}
-
-/* --- Dark: the site's warm inverted tones (--inv-bg #14110f / --inv-fg #fbfaf8) --- */
-.dark {
-  color-scheme: dark;
-
-  --bg: #14110f;          /* warm near-black paper */
-  --surface: #1d1916;     /* lifted warm panel */
-  --ink: #f4efe8;         /* warm off-white */
-  --muted: #a79d94;
-  --faint: #766c64;
-  --line: #2d2723;
-  --accent: #f0714a;      /* brighter coral for dark backgrounds */
-  --accent-ink: #f59a7c;  /* lighter coral for text/hover on dark */
-  --accent-soft: #2a1712; /* dark coral wash */
-  --ok: #57b98d;
-  --err: #ef8a63;
-
-  --track: #2d2723;
-  --thead: #1a1613;
-  --shadow: rgba(0, 0, 0, .4);
-  --scroll-thumb: #3a332e;
-  --tip-bg: #1d1916;
-  --tip-line: #2d2723;
-
-  --op-search-bg: #1a2233; --op-search-fg: #9db6ff; --op-search-line: #2b3a5c;
-  --op-graph-bg: #221a33;  --op-graph-fg: #b9a4f5;  --op-graph-line: #3a2e5c;
-  --op-upsert-bg: #142720; --op-upsert-fg: #57b98d; --op-upsert-line: #24463a;
-}
-
-html, body { padding: 0; margin: 0; }
-body {
-  background: var(--bg);
-  color: var(--ink);
-  font-family: theme('fontFamily.sans');
-  border-top: 3px solid var(--accent);
-  -webkit-font-smoothing: antialiased;
-  transition: background-color .18s ease, color .18s ease;
-}
-::-webkit-scrollbar { width: 10px; height: 10px; }
-::-webkit-scrollbar-thumb { background: var(--scroll-thumb); border-radius: 6px; }
-
-/* Trace op badges — themed via CSS variables so they flip with .dark */
-.op-badge { background: var(--op-search-bg); color: var(--op-search-fg); border-color: var(--op-search-line); }
-.op-search { background: var(--op-search-bg); color: var(--op-search-fg); border-color: var(--op-search-line); }
-.op-graph_search { background: var(--op-graph-bg); color: var(--op-graph-fg); border-color: var(--op-graph-line); }
-.op-upsert { background: var(--op-upsert-bg); color: var(--op-upsert-fg); border-color: var(--op-upsert-line); }
diff --git a/dashboard/app/layout.tsx b/dashboard/app/layout.tsx
deleted file mode 100644
index 735422c..0000000
--- a/dashboard/app/layout.tsx
+++ /dev/null
@@ -1,23 +0,0 @@
-import type { Metadata } from "next";
-import "./globals.css";
-
-export const metadata: Metadata = {
-  title: "dynavec · Observability",
-  description: "Real-time retrieval observability for dynavec — latency, cache, traces.",
-};
-
-// Set the theme class before first paint so there is no light→dark flash.
-// Precedence: ?theme= override (deep-linkable, used for parity screenshots) >
-// saved choice > OS preference; defaults to light (matching the site).
-const themeInit = `(function(){try{var q=new URLSearchParams(location.search).get('theme');var s=localStorage.getItem('dynavec-theme');var d=q?q==='dark':(s?s==='dark':matchMedia('(prefers-color-scheme: dark)').matches);document.documentElement.classList.toggle('dark',d);if(q){try{localStorage.setItem('dynavec-theme',d?'dark':'light');}catch(e){}}}catch(e){}})();`;
-
-export default function RootLayout({ children }: { children: React.ReactNode }) {
-  return (
-    <html lang="en" suppressHydrationWarning>
-      <head>
-        <script dangerouslySetInnerHTML={{ __html: themeInit }} />
-      </head>
-      <body>{children}</body>
-    </html>
-  );
-}
diff --git a/dashboard/app/page.tsx b/dashboard/app/page.tsx
deleted file mode 100644
index 06644a7..0000000
--- a/dashboard/app/page.tsx
+++ /dev/null
@@ -1,61 +0,0 @@
-"use client";
-import { useCallback, useEffect, useState } from "react";
-import Kpis from "@/components/Kpis";
-import LatencyChart from "@/components/LatencyChart";
-import Sidebar from "@/components/Sidebar";
-import TopBar from "@/components/TopBar";
-import TraceDrawer from "@/components/TraceDrawer";
-import TracesTable from "@/components/TracesTable";
-import VolumeChart from "@/components/VolumeChart";
-import { getMetrics, getTrace, getTraces, isLive } from "@/lib/api";
-import type { Metrics, TraceEvent, TraceFilters } from "@/lib/types";
-
-export default function Page() {
-  const [win, setWin] = useState(3600);
-  const [auto, setAuto] = useState(true);
-  const [metrics, setMetrics] = useState<Metrics | null>(null);
-  const [traces, setTraces] = useState<TraceEvent[]>([]);
-  const [filters, setFilters] = useState<TraceFilters>({});
-  const [selected, setSelected] = useState<TraceEvent | null>(null);
-
-  const refresh = useCallback(async () => {
-    const [m, t] = await Promise.all([getMetrics(win), getTraces(filters, 100)]);
-    setMetrics(m);
-    setTraces(t);
-  }, [win, filters]);
-
-  useEffect(() => { refresh(); }, [refresh]);
-  useEffect(() => {
-    if (!auto) return;
-    const id = setInterval(refresh, 4000);
-    return () => clearInterval(id);
-  }, [auto, refresh]);
-
-  return (
-    <>
-      <TopBar window={win} onWindow={setWin} auto={auto} onAuto={() => setAuto((a) => !a)} live={isLive()} />
-      <div className="flex min-h-[calc(100vh-52px)]">
-        <Sidebar />
-        <main className="flex-1 min-w-0 p-6">
-          {metrics && <Kpis m={metrics} />}
-          {metrics && (
-            <div className="grid grid-cols-1 lg:grid-cols-[1.5fr_1fr] gap-4 mb-5">
-              <VolumeChart m={metrics} />
-              <LatencyChart m={metrics} />
-            </div>
-          )}
-          <TracesTable
-            traces={traces}
-            filters={filters}
-            onFilter={setFilters}
-            onSelect={async (id) => setSelected(await getTrace(id))}
-          />
-          <p className="font-mono text-[11.5px] text-faint mt-2">
-            {isLive() ? "Live telemetry from a running dynavec client." : "Sample data — set NEXT_PUBLIC_DYNAVEC_API to a running dynavec.dashboard.serve() endpoint."}
-          </p>
-        </main>
-      </div>
-      <TraceDrawer trace={selected} onClose={() => setSelected(null)} />
-    </>
-  );
-}
diff --git a/dashboard/components/Kpis.tsx b/dashboard/components/Kpis.tsx
deleted file mode 100644
index bd210d5..0000000
--- a/dashboard/components/Kpis.tsx
+++ /dev/null
@@ -1,26 +0,0 @@
-import type { Metrics } from "@/lib/types";
-
-function Kpi({ label, value, unit, win }: { label: string; value: string; unit?: string; win?: boolean }) {
-  return (
-    <div className="bg-surface border border-line rounded-xl2 px-[18px] py-4">
-      <div className="text-[12px] text-muted mb-2">{label}</div>
-      <div className={"font-mono text-[26px] font-bold tracking-tight " + (win ? "text-accent-ink" : "")}>
-        {value}
-        {unit && <span className="text-[13px] text-muted font-normal"> {unit}</span>}
-      </div>
-    </div>
-  );
-}
-
-export default function Kpis({ m }: { m: Metrics }) {
-  const num = (n: number, d = 0) => Number(n).toLocaleString(undefined, { maximumFractionDigits: d });
-  return (
-    <div className="grid grid-cols-2 lg:grid-cols-5 gap-3.5 mb-5">
-      <Kpi label="Queries / min" value={num(m.qpm, 1)} win />
-      <Kpi label="p95 latency" value={num(m.p95, 0)} unit="ms" />
-      <Kpi label="Cache hit rate" value={m.cache_hit_rate == null ? "—" : num(m.cache_hit_rate, 1)} unit={m.cache_hit_rate == null ? "" : "%"} win />
-      <Kpi label="Avg results" value={num(m.avg_results, 1)} />
-      <Kpi label="Error rate" value={num(m.error_rate, 1)} unit="%" />
-    </div>
-  );
-}
diff --git a/dashboard/components/LatencyChart.tsx b/dashboard/components/LatencyChart.tsx
deleted file mode 100644
index 3b1d01b..0000000
--- a/dashboard/components/LatencyChart.tsx
+++ /dev/null
@@ -1,35 +0,0 @@
-"use client";
-import type { Metrics } from "@/lib/types";
-
-const ROWS: [keyof Metrics, string, string][] = [
-  ["p50", "p50", "var(--ok)"],
-  ["p95", "p95", "var(--accent)"],
-  ["p99", "p99", "var(--accent-ink)"],
-];
-
-export default function LatencyChart({ m }: { m: Metrics }) {
-  const max = Math.max(1, m.p99, m.p95, m.p50);
-  return (
-    <div className="bg-surface border border-line rounded-xl2 px-[18px] py-4">
-      <h3 className="m-0 mb-3.5 text-[14px] font-semibold">
-        Latency percentiles <span className="font-mono text-[11px] text-faint font-normal">ms</span>
-      </h3>
-      <div className="flex flex-col gap-3.5 pt-1">
-        {ROWS.map(([k, label, color]) => {
-          const v = m[k] as number;
-          return (
-            <div key={label}>
-              <div className="flex justify-between text-[12px] mb-1">
-                <span className="font-mono" style={{ color }}>{label}</span>
-                <span className="font-mono">{Number(v).toFixed(1)} ms</span>
-              </div>
-              <div className="h-2.5 bg-track rounded-full">
-                <div className="h-full rounded-full" style={{ width: `${(v / max) * 100}%`, background: color }} />
-              </div>
-            </div>
-          );
-        })}
-      </div>
-    </div>
-  );
-}
diff --git a/dashboard/components/Sidebar.tsx b/dashboard/components/Sidebar.tsx
deleted file mode 100644
index 368cdd0..0000000
--- a/dashboard/components/Sidebar.tsx
+++ /dev/null
@@ -1,33 +0,0 @@
-const GROUPS: { title: string; items: { label: string; soon?: boolean; active?: boolean }[] }[] = [
-  { title: "Observability", items: [{ label: "Tracing", active: true }, { label: "Latency" }, { label: "Cost" }] },
-  { title: "Evaluation", items: [{ label: "Scores", soon: true }, { label: "Faithfulness", soon: true }] },
-  { title: "Resources", items: [{ label: "Buckets & Indexes", soon: true }, { label: "Namespaces", soon: true }] },
-];
-
-export default function Sidebar() {
-  return (
-    <nav className="w-[210px] shrink-0 border-r border-line bg-surface p-4 hidden md:block">
-      {GROUPS.map((g) => (
-        <div key={g.title}>
-          <h4 className="font-mono text-[11px] uppercase tracking-wider text-faint mt-4 mb-2 px-2">{g.title}</h4>
-          {g.items.map((it) => (
-            <a
-              key={it.label}
-              className={
-                "flex items-center justify-between px-2.5 py-1.5 rounded-md text-[13.5px] mb-0.5 " +
-                (it.active
-                  ? "bg-accent-soft text-accent-ink font-semibold border-l-2 border-accent"
-                  : it.soon
-                  ? "text-faint cursor-default"
-                  : "text-muted hover:text-ink cursor-pointer")
-              }
-            >
-              {it.label}
-              {it.soon && <span className="font-mono text-[10px] text-faint">soon</span>}
-            </a>
-          ))}
-        </div>
-      ))}
-    </nav>
-  );
-}
diff --git a/dashboard/components/ThemeToggle.tsx b/dashboard/components/ThemeToggle.tsx
deleted file mode 100644
index afce800..0000000
--- a/dashboard/components/ThemeToggle.tsx
+++ /dev/null
@@ -1,46 +0,0 @@
-"use client";
-import { useEffect, useState } from "react";
-
-// Toggles the `.dark` class on <html> and persists the choice. The initial
-// class is set pre-paint by the inline script in app/layout.tsx (no flash);
-// this component only syncs its icon to that state and flips it on click.
-export default function ThemeToggle() {
-  const [dark, setDark] = useState(false);
-
-  useEffect(() => {
-    setDark(document.documentElement.classList.contains("dark"));
-  }, []);
-
-  const toggle = () => {
-    const next = !document.documentElement.classList.contains("dark");
-    document.documentElement.classList.toggle("dark", next);
-    try {
-      localStorage.setItem("dynavec-theme", next ? "dark" : "light");
-    } catch {
-      /* storage may be unavailable */
-    }
-    setDark(next);
-  };
-
-  return (
-    <button
-      onClick={toggle}
-      aria-label={dark ? "Switch to light theme" : "Switch to dark theme"}
-      title={dark ? "Light" : "Dark"}
-      className="grid place-items-center w-8 h-8 border-[1.5px] border-ink rounded-lg bg-surface text-ink hover:text-accent"
-    >
-      {dark ? (
-        // sun
-        <svg width="15" height="15" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="1.8" strokeLinecap="round">
-          <circle cx="12" cy="12" r="4.2" />
-          <path d="M12 2v2.5M12 19.5V22M2 12h2.5M19.5 12H22M4.9 4.9l1.8 1.8M17.3 17.3l1.8 1.8M19.1 4.9l-1.8 1.8M6.7 17.3l-1.8 1.8" />
-        </svg>
-      ) : (
-        // moon
-        <svg width="15" height="15" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="1.8" strokeLinecap="round" strokeLinejoin="round">
-          <path d="M20 14.5A8 8 0 1 1 9.5 4a6.2 6.2 0 0 0 10.5 10.5z" />
-        </svg>
-      )}
-    </button>
-  );
-}
diff --git a/dashboard/components/TopBar.tsx b/dashboard/components/TopBar.tsx
deleted file mode 100644
index 3191d5c..0000000
--- a/dashboard/components/TopBar.tsx
+++ /dev/null
@@ -1,65 +0,0 @@
-"use client";
-import ThemeToggle from "@/components/ThemeToggle";
-
-const RANGES = [
-  { label: "30m", w: 1800 },
-  { label: "1h", w: 3600 },
-  { label: "6h", w: 21600 },
-  { label: "24h", w: 86400 },
-];
-
-export default function TopBar({
-  window: win, onWindow, auto, onAuto, live,
-}: {
-  window: number;
-  onWindow: (w: number) => void;
-  auto: boolean;
-  onAuto: () => void;
-  live: boolean;
-}) {
-  return (
-    <header className="flex items-center gap-4 px-5 py-3 bg-surface border-b border-line sticky top-0 z-10">
-      <span className="flex items-center gap-2.5 font-mono font-bold text-[16px]">
-        <svg width="18" height="18" viewBox="0 0 22 22" className="text-accent">
-          <rect x="1" y="1" width="20" height="20" fill="none" stroke="currentColor" strokeWidth="1.5" />
-          <line x1="1" y1="11" x2="21" y2="11" stroke="currentColor" strokeWidth="1.5" />
-          <line x1="11" y1="1" x2="11" y2="21" stroke="currentColor" strokeWidth="1.5" />
-          <circle cx="6" cy="6" r="2" fill="currentColor" />
-          <circle cx="16" cy="16" r="2" fill="currentColor" />
-        </svg>
-        dynavec
-      </span>
-      <span className="text-muted text-[13px] mr-auto">
-        Observability{" "}
-        <span className={"font-mono text-[11px] " + (live ? "text-ok" : "text-accent-ink")}>
-          · {live ? "live" : "sample data"}
-        </span>
-      </span>
-
-      <div className="flex border-[1.5px] border-ink rounded-lg overflow-hidden">
-        {RANGES.map((r) => (
-          <button
-            key={r.w}
-            onClick={() => onWindow(r.w)}
-            className={
-              "font-mono text-[12px] px-3 py-1.5 border-r border-line last:border-r-0 " +
-              (win === r.w ? "bg-accent text-white" : "bg-surface text-muted hover:text-ink")
-            }
-          >
-            {r.label}
-          </button>
-        ))}
-      </div>
-      <button
-        onClick={onAuto}
-        className={
-          "font-mono text-[12px] border-[1.5px] border-ink rounded-lg px-3 py-1.5 " +
-          (auto ? "bg-ink text-bg" : "bg-surface text-ink")
-        }
-      >
-        Auto-refresh
-      </button>
-      <ThemeToggle />
-    </header>
-  );
-}
diff --git a/dashboard/components/TraceDrawer.tsx b/dashboard/components/TraceDrawer.tsx
deleted file mode 100644
index d31abd3..0000000
--- a/dashboard/components/TraceDrawer.tsx
+++ /dev/null
@@ -1,54 +0,0 @@
-"use client";
-import type { TraceEvent } from "@/lib/types";
-
-function Row({ k, v }: { k: string; v: React.ReactNode }) {
-  return (
-    <>
-      <div className="font-mono text-[12px] text-muted">{k}</div>
-      <div className="tabular-nums break-words">{v == null || v === "" ? "—" : v}</div>
-    </>
-  );
-}
-
-export default function TraceDrawer({ trace, onClose }: { trace: TraceEvent | null; onClose: () => void }) {
-  return (
-    <div
-      className={
-        "fixed top-0 right-0 h-screen w-[min(460px,92vw)] bg-surface border-l border-line shadow-card z-20 overflow-y-auto p-[22px] transition-transform duration-200 " +
-        (trace ? "translate-x-0" : "translate-x-full")
-      }
-    >
-      <button onClick={onClose} className="absolute top-4 right-[18px] text-[20px] text-muted">×</button>
-      {trace && (
-        <>
-          <h3 className="m-0 mb-1 text-[16px] font-semibold">
-            <span className="font-mono text-[11px] px-2 py-0.5 rounded-full border border-line mr-2">{trace.op}</span>
-            trace
-          </h3>
-          <div className="font-mono text-[12px] text-muted">
-            {trace.id} · {new Date(trace.ts * 1000).toLocaleString()}
-          </div>
-          <div className="grid grid-cols-[130px_1fr] gap-x-3.5 gap-y-2 mt-4 text-[13px]">
-            <Row k="Namespace" v={trace.namespace} />
-            <Row k="Latency" v={`${trace.latency_ms.toFixed(2)} ms`} />
-            <Row k="Results" v={trace.n_results} />
-            <Row k="top_k" v={trace.top_k} />
-            <Row k="Cache" v={trace.cache_hit == null ? "no cache" : trace.cache_hit ? "hit" : "miss"} />
-            <Row k="Filtered" v={String(trace.filtered)} />
-            <Row k="Rescore" v={trace.rescore} />
-            <Row k="Rerank" v={trace.rerank} />
-            <Row k="Top score" v={trace.score_top} />
-            <Row k="Mean score" v={trace.score_mean} />
-            <Row k="Status" v={trace.status} />
-            {trace.error && <Row k="Error" v={trace.error} />}
-            {trace.query_preview && <Row k="Query" v={trace.query_preview} />}
-          </div>
-          <div className="mt-[18px]">
-            <div className="font-mono text-[12px] text-muted mb-1.5">End-to-end latency</div>
-            <div className="h-2.5 rounded-full bg-accent" />
-          </div>
-        </>
-      )}
-    </div>
-  );
-}
diff --git a/dashboard/components/TracesTable.tsx b/dashboard/components/TracesTable.tsx
deleted file mode 100644
index 1797e13..0000000
--- a/dashboard/components/TracesTable.tsx
+++ /dev/null
@@ -1,93 +0,0 @@
-"use client";
-import type { TraceEvent, TraceFilters } from "@/lib/types";
-
-// Themed via CSS-variable classes in globals.css so badges flip with `.dark`.
-const OP_CLASS: Record<string, string> = {
-  search: "op-search",
-  graph_search: "op-graph_search",
-  upsert: "op-upsert",
-};
-
-export default function TracesTable({
-  traces, filters, onFilter, onSelect,
-}: {
-  traces: TraceEvent[];
-  filters: TraceFilters;
-  onFilter: (f: TraceFilters) => void;
-  onSelect: (id: string) => void;
-}) {
-  return (
-    <div className="bg-surface border border-line rounded-xl2 overflow-hidden">
-      <div className="flex items-center gap-3 px-[18px] py-3.5 border-b border-line">
-        <h3 className="m-0 text-[14px] font-semibold">Traces</h3>
-        <div className="ml-auto flex gap-2">
-          <select
-            value={filters.op || ""}
-            onChange={(e) => onFilter({ ...filters, op: e.target.value })}
-            className="font-mono text-[12px] border border-line rounded-md px-2.5 py-1.5 bg-bg"
-          >
-            <option value="">all ops</option>
-            <option value="search">search</option>
-            <option value="graph_search">graph_search</option>
-            <option value="upsert">upsert</option>
-          </select>
-          <select
-            value={filters.status || ""}
-            onChange={(e) => onFilter({ ...filters, status: e.target.value })}
-            className="font-mono text-[12px] border border-line rounded-md px-2.5 py-1.5 bg-bg"
-          >
-            <option value="">any status</option>
-            <option value="ok">ok</option>
-            <option value="error">error</option>
-          </select>
-          <input
-            placeholder="namespace…"
-            value={filters.namespace || ""}
-            onChange={(e) => onFilter({ ...filters, namespace: e.target.value })}
-            className="font-mono text-[12px] border border-line rounded-md px-2.5 py-1.5 bg-bg w-28"
-          />
-        </div>
-      </div>
-
-      {traces.length === 0 ? (
-        <div className="p-10 text-center text-muted">No traces match.</div>
-      ) : (
-        <div className="overflow-x-auto">
-          <table className="w-full border-collapse text-[13px]">
-            <thead>
-              <tr className="text-left font-mono text-[11px] uppercase tracking-wide text-muted bg-thead">
-                {["Start", "Op", "Namespace", "Latency", "Results", "Cache", "Rank", "Status"].map((h) => (
-                  <th key={h} className="px-[18px] py-2.5 border-b border-line font-normal">{h}</th>
-                ))}
-              </tr>
-            </thead>
-            <tbody>
-              {traces.map((e) => (
-                <tr
-                  key={e.id}
-                  onClick={() => onSelect(e.id)}
-                  className="cursor-pointer hover:bg-accent-soft [&>td]:px-[18px] [&>td]:py-2.5 [&>td]:border-b [&>td]:border-line tabular-nums"
-                >
-                  <td className="font-mono">{new Date(e.ts * 1000).toLocaleTimeString()}</td>
-                  <td>
-                    <span className={"font-mono text-[11px] px-2 py-0.5 rounded-full border " + (OP_CLASS[e.op] || "border-line")}>
-                      {e.op}
-                    </span>
-                  </td>
-                  <td>{e.namespace}</td>
-                  <td className="font-mono">{e.latency_ms.toFixed(1)} ms</td>
-                  <td className="font-mono">{e.n_results}</td>
-                  <td>
-                    {e.cache_hit == null ? <span className="text-faint">—</span> : e.cache_hit ? <span className="text-ok">hit</span> : <span className="text-muted">miss</span>}
-                  </td>
-                  <td className="font-mono">{[e.rescore, e.rerank].filter(Boolean).join("+") || <span className="text-faint">—</span>}</td>
-                  <td className={e.status === "error" ? "text-err font-semibold" : "text-ok"}>{e.status}</td>
-                </tr>
-              ))}
-            </tbody>
-          </table>
-        </div>
-      )}
-    </div>
-  );
-}
diff --git a/dashboard/components/VolumeChart.tsx b/dashboard/components/VolumeChart.tsx
deleted file mode 100644
index efd309e..0000000
--- a/dashboard/components/VolumeChart.tsx
+++ /dev/null
@@ -1,31 +0,0 @@
-"use client";
-import { Bar, BarChart, ResponsiveContainer, Tooltip, XAxis } from "recharts";
-import type { Metrics } from "@/lib/types";
-
-export default function VolumeChart({ m }: { m: Metrics }) {
-  const data = m.histogram.map((count, i) => ({ i, count }));
-  return (
-    <div className="bg-surface border border-line rounded-xl2 px-[18px] py-4">
-      <h3 className="m-0 mb-3.5 text-[14px] font-semibold">
-        Query volume{" "}
-        <span className="font-mono text-[11px] text-faint font-normal">
-          {m.total} traces · {Math.round(m.bucket_width_s)}s buckets
-        </span>
-      </h3>
-      <div style={{ width: "100%", height: 150 }}>
-        <ResponsiveContainer>
-          <BarChart data={data} margin={{ top: 4, right: 4, bottom: 0, left: 0 }}>
-            <XAxis dataKey="i" hide />
-            <Tooltip
-              cursor={{ fill: "var(--accent-soft)" }}
-              contentStyle={{ fontFamily: "JetBrains Mono", fontSize: 12, background: "var(--tip-bg)", color: "var(--ink)", border: "1px solid var(--tip-line)", borderRadius: 8 }}
-              labelFormatter={() => ""}
-              formatter={(v: number) => [v, "queries"]}
-            />
-            <Bar dataKey="count" fill="var(--accent)" radius={[2, 2, 0, 0]} />
-          </BarChart>
-        </ResponsiveContainer>
-      </div>
-    </div>
-  );
-}
diff --git a/dashboard/lib/api.ts b/dashboard/lib/api.ts
deleted file mode 100644
index ea6bef3..0000000
--- a/dashboard/lib/api.ts
+++ /dev/null
@@ -1,54 +0,0 @@
-import type { Metrics, TraceEvent, TraceFilters } from "./types";
-import { mockMetrics, mockTraces } from "./mock";
-
-// Point this at a running `dynavec.dashboard.serve(recorder)` API.
-// Falls back to sample data when unset or unreachable (dev / static preview).
-const API_BASE = process.env.NEXT_PUBLIC_DYNAVEC_API || "";
-
-let _mockTraces: TraceEvent[] | null = null;
-function sampleTraces(): TraceEvent[] {
-  if (!_mockTraces) _mockTraces = mockTraces(60);
-  return _mockTraces;
-}
-
-export function isLive(): boolean {
-  return Boolean(API_BASE);
-}
-
-export async function getMetrics(windowSeconds: number): Promise<Metrics> {
-  if (API_BASE) {
-    try {
-      const r = await fetch(`${API_BASE}/api/metrics?window=${windowSeconds}`, { cache: "no-store" });
-      if (r.ok) return (await r.json()) as Metrics;
-    } catch { /* fall through to sample */ }
-  }
-  return mockMetrics(sampleTraces());
-}
-
-export async function getTraces(filters: TraceFilters, limit = 100): Promise<TraceEvent[]> {
-  if (API_BASE) {
-    try {
-      const q = new URLSearchParams({ limit: String(limit) });
-      if (filters.op) q.set("op", filters.op);
-      if (filters.status) q.set("status", filters.status);
-      if (filters.namespace) q.set("namespace", filters.namespace);
-      const r = await fetch(`${API_BASE}/api/traces?${q}`, { cache: "no-store" });
-      if (r.ok) return (await r.json()) as TraceEvent[];
-    } catch { /* fall through */ }
-  }
-  return sampleTraces().filter((e) =>
-    (!filters.op || e.op === filters.op) &&
-    (!filters.status || e.status === filters.status) &&
-    (!filters.namespace || e.namespace.includes(filters.namespace)),
-  );
-}
-
-export async function getTrace(id: string): Promise<TraceEvent | null> {
-  if (API_BASE) {
-    try {
-      const r = await fetch(`${API_BASE}/api/trace/${id}`, { cache: "no-store" });
-      if (r.ok) return (await r.json()) as TraceEvent;
-    } catch { /* fall through */ }
-  }
-  return sampleTraces().find((e) => e.id === id) || null;
-}
diff --git a/dashboard/lib/mock.ts b/dashboard/lib/mock.ts
deleted file mode 100644
index 310f075..0000000
--- a/dashboard/lib/mock.ts
+++ /dev/null
@@ -1,77 +0,0 @@
-import type { Metrics, TraceEvent } from "./types";
-
-// Deterministic-ish sample data so the dashboard renders standalone (dev, static
-// export, first run) before it is pointed at a live dynavec telemetry API.
-const NS = ["kb", "tenant-a", "tenant-b"];
-const OPS = ["search", "search", "search", "graph_search", "upsert"];
-const RANK = [null, null, "cosine", "mmr", "dot"];
-
-let seed = 42;
-function rand() {
-  seed = (seed * 1103515245 + 12345) & 0x7fffffff;
-  return seed / 0x7fffffff;
-}
-function pick<T>(a: T[]): T {
-  return a[Math.floor(rand() * a.length)];
-}
-
-export function mockTraces(n = 60): TraceEvent[] {
-  const now = Date.now() / 1000;
-  const out: TraceEvent[] = [];
-  for (let i = 0; i < n; i++) {
-    const op = pick(OPS);
-    const cacheHit = op === "upsert" ? null : rand() > 0.35;
-    const lat = op === "upsert" ? 8 + rand() * 30 : (cacheHit ? 6 + rand() * 12 : 60 + rand() * 90);
-    const nres = op === "upsert" ? 0 : pick([5, 10, 10, 20]);
-    out.push({
-      id: Math.random().toString(16).slice(2, 14),
-      ts: now - i * 3,
-      op,
-      namespace: pick(NS),
-      latency_ms: Math.round(lat * 100) / 100,
-      n_results: nres,
-      top_k: op === "upsert" ? null : nres,
-      cache_hit: cacheHit,
-      filtered: rand() > 0.6,
-      rescore: op === "search" ? pick(RANK) : null,
-      rerank: rand() > 0.7 ? "mmr" : null,
-      score_top: op === "upsert" ? null : Math.round((0.7 + rand() * 0.29) * 1000) / 1000,
-      score_mean: op === "upsert" ? null : Math.round((0.5 + rand() * 0.3) * 1000) / 1000,
-      status: rand() > 0.98 ? "error" : "ok",
-      error: null,
-      query_preview: op === "upsert" ? null : pick(["apple pie recipe", "rocket to mars", "serverless vectors on aws", "embedding models"]),
-    });
-  }
-  return out;
-}
-
-export function mockMetrics(traces: TraceEvent[]): Metrics {
-  const win = traces;
-  const lat = win.filter((e) => e.status === "ok").map((e) => e.latency_ms).sort((a, b) => a - b);
-  const pct = (p: number) => (lat.length ? lat[Math.min(lat.length - 1, Math.floor((lat.length - 1) * p))] : 0);
-  const cacheScoped = win.filter((e) => e.cache_hit !== null);
-  const hits = cacheScoped.filter((e) => e.cache_hit).length;
-  const buckets = 30;
-  const hist = new Array(buckets).fill(0);
-  win.forEach((_, i) => { hist[Math.min(buckets - 1, Math.floor((i / win.length) * buckets))]++; });
-  const op_mix: Record<string, number> = {};
-  win.forEach((e) => { op_mix[e.op] = (op_mix[e.op] || 0) + 1; });
-  return {
-    total: win.length,
-    qpm: Math.round((win.length / 60) * 100) / 100 * 6,
-    p50: Math.round(pct(0.5) * 100) / 100,
-    p95: Math.round(pct(0.95) * 100) / 100,
-    p99: Math.round(pct(0.99) * 100) / 100,
-    cache_hit_rate: cacheScoped.length ? Math.round((1000 * hits) / cacheScoped.length) / 10 : null,
-    cache_hits: hits,
-    cache_total: cacheScoped.length,
-    error_rate: Math.round((1000 * win.filter((e) => e.status === "error").length) / Math.max(1, win.length)) / 10,
-    avg_results: Math.round((10 * win.reduce((s, e) => s + e.n_results, 0)) / Math.max(1, win.length)) / 10,
-    op_mix,
-    namespaces: {},
-    histogram: hist,
-    bucket_width_s: 120,
-    window_start: 0,
-    window_seconds: 3600,
-  };
-}
diff --git a/dashboard/lib/types.ts b/dashboard/lib/types.ts
deleted file mode 100644
index f4d4ea7..0000000
--- a/dashboard/lib/types.ts
+++ /dev/null
@@ -1,48 +0,0 @@
-export interface Metrics {
-  total: number;
-  qpm: number;
-  p50: number;
-  p95: number;
-  p99: number;
-  cache_hit_rate: number | null;
-  cache_hits: number;
-  cache_total: number;
-  error_rate: number;
-  avg_results: number;
-  op_mix: Record<string, number>;
-  namespaces: Record<string, number>;
-  histogram: number[];
-  bucket_width_s: number;
-  window_start: number;
-  window_seconds: number;
-}
-
-export interface TraceEvent {
-  id: string;
-  ts: number;
-  op: string;
-  namespace: string;
-  latency_ms: number;
-  n_results: number;
-  top_k: number | null;
-  cache_hit: boolean | null;
-  filtered: boolean;
-  rescore: string | null;
-  rerank: string | null;
-  score_top: number | null;
-  score_mean: number | null;
-  status: string;
-  error: string | null;
-  query_preview: string | null;
-  eval_faithfulness?: number | null;
-  eval_relevance?: number | null;
-  eval_recall?: number | null;
-  eval_mrr?: number | null;
-  eval_ndcg?: number | null;
-}
-
-export interface TraceFilters {
-  op?: string;
-  status?: string;
-  namespace?: string;
-}
diff --git a/dashboard/next.config.mjs b/dashboard/next.config.mjs
deleted file mode 100644
index b24813c..0000000
--- a/dashboard/next.config.mjs
+++ /dev/null
@@ -1,11 +0,0 @@
-/** @type {import('next').NextConfig} */
-const nextConfig = {
-  // Static export so the dashboard can be served by any static host (incl. the
-  // Python `serve()` or GitHub Pages). Data is fetched client-side at runtime.
-  output: "export",
-  images: { unoptimized: true },
-  // Set NEXT_PUBLIC_BASE_PATH="/dynavec/dashboard" when deploying under a subpath.
-  basePath: process.env.NEXT_PUBLIC_BASE_PATH || "",
-  trailingSlash: true,
-};
-export default nextConfig;
diff --git a/dashboard/package-lock.json b/dashboard/package-lock.json
deleted file mode 100644
index d87f4fb..0000000
--- a/dashboard/package-lock.json
+++ /dev/null
@@ -1,2019 +0,0 @@
-{
-  "name": "dynavec-dashboard",
-  "version": "0.1.0",
-  "lockfileVersion": 3,
-  "requires": true,
-  "packages": {
-    "": {
-      "name": "dynavec-dashboard",
-      "version": "0.1.0",
-      "dependencies": {
-        "next": "^14.2.35",
-        "react": "18.3.1",
-        "react-dom": "18.3.1",
-        "recharts": "2.12.7"
-      },
-      "devDependencies": {
-        "@types/node": "20.14.10",
-        "@types/react": "18.3.3",
-        "@types/react-dom": "18.3.0",
-        "autoprefixer": "10.4.19",
-        "postcss": "8.4.39",
-        "tailwindcss": "3.4.6",
-        "typescript": "5.5.3"
-      }
-    },
-    "node_modules/@alloc/quick-lru": {
-      "version": "5.3.0",
-      "resolved": "https://registry.npmjs.org/@alloc/quick-lru/-/quick-lru-5.3.0.tgz",
-      "integrity": "sha512-U4+70Pc5ZS9osnCBCE5Jha/ciHM+Yp+CNMNC/7HvYbNRk1Ldd+f7qO65W5qfhu/TCv+/ozljlXXe9Nj8419DMA==",
-      "dev": true,
-      "license": "MIT",
-      "engines": {
-        "node": ">=10"
-      },
-      "funding": {
-        "url": "https://github.com/sponsors/sindresorhus"
-      }
-    },
-    "node_modules/@babel/runtime": {
-      "version": "7.29.7",
-      "resolved": "https://registry.npmjs.org/@babel/runtime/-/runtime-7.29.7.tgz",
-      "integrity": "sha512-Nq8OhGWiZIZGV6hLHoyAKLLcJihP/xFeBMGJoUrxTX2psI8dCifzLhZISFb+VWS3wFMRDmCGw5R+dOySCqPLhw==",
-      "license": "MIT",
-      "engines": {
-        "node": ">=6.9.0"
-      }
-    },
-    "node_modules/@jridgewell/gen-mapping": {
-      "version": "0.3.13",
-      "resolved": "https://registry.npmjs.org/@jridgewell/gen-mapping/-/gen-mapping-0.3.13.tgz",
-      "integrity": "sha512-2kkt/7niJ6MgEPxF0bYdQ6etZaA+fQvDcLKckhy1yIQOzaoKjBBjSj63/aLVjYE3qhRt5dvM+uUyfCg6UKCBbA==",
-      "dev": true,
-      "license": "MIT",
-      "dependencies": {
-        "@jridgewell/sourcemap-codec": "^1.5.0",
-        "@jridgewell/trace-mapping": "^0.3.24"
-      }
-    },
-    "node_modules/@jridgewell/resolve-uri": {
-      "version": "3.1.2",
-      "resolved": "https://registry.npmjs.org/@jridgewell/resolve-uri/-/resolve-uri-3.1.2.tgz",
-      "integrity": "sha512-bRISgCIjP20/tbWSPWMEi54QVPRZExkuD9lJL+UIxUKtwVJA8wW1Trb1jMs1RFXo1CBTNZ/5hpC9QvmKWdopKw==",
-      "dev": true,
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-      "dev": true,
-      "license": "Apache-2.0"
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-      "license": "Apache-2.0",
-      "bin": {
-        "tsc": "bin/tsc",
-        "tsserver": "bin/tsserver"
-      },
-      "engines": {
-        "node": ">=14.17"
-      }
-    },
-    "node_modules/undici-types": {
-      "version": "5.26.5",
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-      "dev": true,
-      "license": "MIT"
-    },
-    "node_modules/update-browserslist-db": {
-      "version": "1.3.2",
-      "resolved": "https://registry.npmjs.org/update-browserslist-db/-/update-browserslist-db-1.3.2.tgz",
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-      "dev": true,
-      "funding": [
-        {
-          "type": "opencollective",
-          "url": "https://opencollective.com/browserslist"
-        },
-        {
-          "type": "tidelift",
-          "url": "https://tidelift.com/funding/github/npm/browserslist"
-        },
-        {
-          "type": "github",
-          "url": "https://github.com/sponsors/ai"
-        }
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-      "license": "MIT",
-      "dependencies": {
-        "escalade": "^3.2.0",
-        "picocolors": "^1.1.1"
-      },
-      "bin": {
-        "update-browserslist-db": "cli.js"
-      },
-      "peerDependencies": {
-        "browserslist": ">= 4.21.0"
-      }
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-      "license": "MIT"
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-        "@types/d3-ease": "^3.0.0",
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-        "d3-timer": "^3.0.1"
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-      "resolved": "https://registry.npmjs.org/yaml/-/yaml-2.9.0.tgz",
-      "integrity": "sha512-2AvhNX3mb8zd6Zy7INTtSpl1F15HW6Wnqj0srWlkKLcpYl/gMIMJiyuGq2KeI2YFxUPjdlB+3Lc10seMLtL4cA==",
-      "dev": true,
-      "license": "ISC",
-      "bin": {
-        "yaml": "bin.mjs"
-      },
-      "engines": {
-        "node": ">= 14.6"
-      },
-      "funding": {
-        "url": "https://github.com/sponsors/eemeli"
-      }
-    }
-  }
-}
diff --git a/dashboard/package.json b/dashboard/package.json
deleted file mode 100644
index 5291342..0000000
--- a/dashboard/package.json
+++ /dev/null
@@ -1,27 +0,0 @@
-{
-  "name": "dynavec-dashboard",
-  "version": "0.1.0",
-  "private": true,
-  "description": "dynavec observability dashboard — Next.js + Recharts, dynavec brand theme.",
-  "scripts": {
-    "dev": "next dev -p 3000",
-    "build": "next build",
-    "start": "next start -p 3000",
-    "lint": "next lint"
-  },
-  "dependencies": {
-    "next": "^14.2.35",
-    "react": "18.3.1",
-    "react-dom": "18.3.1",
-    "recharts": "2.12.7"
-  },
-  "devDependencies": {
-    "@types/node": "20.14.10",
-    "@types/react": "18.3.3",
-    "@types/react-dom": "18.3.0",
-    "autoprefixer": "10.4.19",
-    "postcss": "8.4.39",
-    "tailwindcss": "3.4.6",
-    "typescript": "5.5.3"
-  }
-}
diff --git a/dashboard/postcss.config.mjs b/dashboard/postcss.config.mjs
deleted file mode 100644
index 2aa7205..0000000
--- a/dashboard/postcss.config.mjs
+++ /dev/null
@@ -1,6 +0,0 @@
-export default {
-  plugins: {
-    tailwindcss: {},
-    autoprefixer: {},
-  },
-};
diff --git a/dashboard/tailwind.config.ts b/dashboard/tailwind.config.ts
deleted file mode 100644
index fb8ca35..0000000
--- a/dashboard/tailwind.config.ts
+++ /dev/null
@@ -1,41 +0,0 @@
-import type { Config } from "tailwindcss";
-
-// dynavec brand tokens — kept in sync with the landing page (styles.css).
-// Values are driven by CSS variables (see app/globals.css) so a single
-// `.dark` class on <html> flips the whole palette. Light is the default,
-// matching the landing site; dark uses the site's warm inverted tones.
-const config: Config = {
-  darkMode: "class",
-  content: ["./app/**/*.{ts,tsx}", "./components/**/*.{ts,tsx}"],
-  theme: {
-    extend: {
-      colors: {
-        bg: "var(--bg)",
-        surface: "var(--surface)",
-        ink: "var(--ink)",
-        muted: "var(--muted)",
-        faint: "var(--faint)",
-        line: "var(--line)",
-        accent: "var(--accent)",
-        "accent-ink": "var(--accent-ink)",
-        "accent-soft": "var(--accent-soft)",
-        ok: "var(--ok)",
-        err: "var(--err)",
-        track: "var(--track)",
-        thead: "var(--thead)",
-      },
-      fontFamily: {
-        sans: ['Inter', 'ui-sans-serif', 'system-ui', 'sans-serif'],
-        mono: ['"JetBrains Mono"', 'ui-monospace', 'Menlo', 'monospace'],
-      },
-      boxShadow: {
-        card: "0 6px 30px var(--shadow)",
-      },
-      borderRadius: {
-        xl2: "14px",
-      },
-    },
-  },
-  plugins: [],
-};
-export default config;
diff --git a/dashboard/tsconfig.json b/dashboard/tsconfig.json
deleted file mode 100644
index f5fc2f7..0000000
--- a/dashboard/tsconfig.json
+++ /dev/null
@@ -1,21 +0,0 @@
-{
-  "compilerOptions": {
-    "target": "ES2020",
-    "lib": ["dom", "dom.iterable", "esnext"],
-    "allowJs": true,
-    "skipLibCheck": true,
-    "strict": true,
-    "noEmit": true,
-    "esModuleInterop": true,
-    "module": "esnext",
-    "moduleResolution": "bundler",
-    "resolveJsonModule": true,
-    "isolatedModules": true,
-    "jsx": "preserve",
-    "incremental": true,
-    "plugins": [{ "name": "next" }],
-    "paths": { "@/*": ["./*"] }
-  },
-  "include": ["next-env.d.ts", "**/*.ts", "**/*.tsx", ".next/types/**/*.ts"],
-  "exclude": ["node_modules"]
-}
diff --git a/examples/ingest_office_docs.py b/examples/ingest_office_docs.py
index ab457af..222388c 100644
--- a/examples/ingest_office_docs.py
+++ b/examples/ingest_office_docs.py
@@ -1,9 +1,11 @@
 """Example: Ingesting Word (.docx), PowerPoint (.pptx), and Excel (.xlsx) files into dynavec."""
 
 from pathlib import Path
+
 from dynavec import Dynavec, DynavecConfig
 from dynavec.ingest import DocxSource, PptxSource, XlsxSource, ingest
 
+
 def main():
     cfg = DynavecConfig(
         vector_bucket="my-vectors",
diff --git a/get_ci_logs.py b/get_ci_logs.py
new file mode 100644
index 0000000..d1387af
--- /dev/null
+++ b/get_ci_logs.py
@@ -0,0 +1,32 @@
+import urllib.request
+import json
+import sys
+
+def run():
+    url = 'https://api.github.com/repos/ramashishmaurya/dynavec/actions/runs'
+    req = urllib.request.Request(url, headers={'User-Agent': 'Mozilla/5.0'})
+    with urllib.request.urlopen(req) as response:
+        runs = json.loads(response.read().decode())
+    
+    run_info = runs['workflow_runs'][0]
+    
+    jobs_url = run_info['jobs_url']
+    req = urllib.request.Request(jobs_url, headers={'User-Agent': 'Mozilla/5.0'})
+    with urllib.request.urlopen(req) as response:
+        jobs = json.loads(response.read().decode())['jobs']
+        
+    for job in jobs:
+        if job['conclusion'] == 'failure' and 'typecheck' in job['name'].lower():
+            print(f"\n--- FAILED JOB: {job['name']} ---")
+            log_url = f"https://api.github.com/repos/ramashishmaurya/dynavec/actions/jobs/{job['id']}/logs"
+            try:
+                req = urllib.request.Request(log_url, headers={'User-Agent': 'Mozilla/5.0'})
+                with urllib.request.urlopen(req) as log_resp:
+                    log_text = log_resp.read().decode('utf-8')
+                    # Print the last 50 lines of the log
+                    print("\n".join(log_text.splitlines()[-50:]))
+            except Exception as e:
+                print("Could not fetch log:", e)
+
+if __name__ == '__main__':
+    run()
diff --git a/notebooks/rrf_weight_fitting.ipynb b/notebooks/rrf_weight_fitting.ipynb
index 48ed87e..85c381d 100644
--- a/notebooks/rrf_weight_fitting.ipynb
+++ b/notebooks/rrf_weight_fitting.ipynb
@@ -2,6 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
+   "id": "7fb27b941602401d91542211134fc71a",
    "metadata": {},
    "source": [
     "# Fitting RRF / Blend Weights from Labeled Data\n",
@@ -15,6 +16,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "acae54e37e7d407bbb7b55eff062a284",
    "metadata": {},
    "source": [
     "## 1. Imports"
@@ -23,16 +25,18 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "9a63283cbaf04dbcab1f6479b197f3a8",
    "metadata": {},
    "outputs": [],
    "source": [
-    "from dynavec import RRFWeightFitter, FitResult\n",
+    "from dynavec import FitResult, RRFWeightFitter\n",
     "from dynavec.eval import LabeledQuery\n",
     "from dynavec.models import SearchResult"
    ]
   },
   {
    "cell_type": "markdown",
+   "id": "8dd0d8092fe74a7c96281538738b07e2",
    "metadata": {},
    "source": [
     "## 2. Create synthetic retriever results\n",
@@ -48,12 +52,45 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "72eea5119410473aa328ad9291626812",
    "metadata": {},
    "outputs": [],
-   "source": "def r(doc_id, score):\n    return SearchResult(id=doc_id, score=score)\n\n# Each list = results for one query from that retriever\n# Shape: [retriever][query_index] -> list[SearchResult]\n\ndense_results = [\n    # query 0: \"FD interest rate\" — dense puts doc_fd first ✓\n    [r(\"doc_fd\", 0.95), r(\"doc_savings\", 0.60), r(\"doc_noise\", 0.20)],\n    # query 1: \"how to open savings account\" — dense puts doc_savings first ✓\n    [r(\"doc_savings\", 0.90), r(\"doc_loan\", 0.50), r(\"doc_noise\", 0.15)],\n    # query 2: \"home loan EMI calculator\" — dense puts doc_loan first ✓\n    [r(\"doc_loan\", 0.88), r(\"doc_fd\", 0.40), r(\"doc_noise\", 0.10)],\n    # query 3: \"UPI transaction limit\" — both retrievers agree ✓\n    [r(\"doc_upi\", 0.92), r(\"doc_fd\", 0.45), r(\"doc_savings\", 0.20)],\n]\n\nsparse_results = [\n    # query 0: sparse buries doc_fd at rank 2 — noisy keyword match ✗\n    [r(\"doc_savings\", 0.80), r(\"doc_noise\", 0.50), r(\"doc_fd\", 0.20)],\n    # query 1: sparse buries doc_savings at rank 2 ✗\n    [r(\"doc_loan\", 0.75), r(\"doc_noise\", 0.45), r(\"doc_savings\", 0.15)],\n    # query 2: sparse buries doc_loan at rank 2 ✗\n    [r(\"doc_fd\", 0.70), r(\"doc_noise\", 0.40), r(\"doc_loan\", 0.10)],\n    # query 3: sparse also gets this right ✓\n    [r(\"doc_upi\", 0.85), r(\"doc_fd\", 0.40), r(\"doc_savings\", 0.20)],\n]\n\nprint(f\"Retrievers: 2\")\nprint(f\"Queries: {len(dense_results)}\")"
+   "source": [
+    "def r(doc_id, score):\n",
+    "    return SearchResult(id=doc_id, score=score)\n",
+    "\n",
+    "# Each list = results for one query from that retriever\n",
+    "# Shape: [retriever][query_index] -> list[SearchResult]\n",
+    "\n",
+    "dense_results = [\n",
+    "    # query 0: \"FD interest rate\" — dense puts doc_fd first ✓\n",
+    "    [r(\"doc_fd\", 0.95), r(\"doc_savings\", 0.60), r(\"doc_noise\", 0.20)],\n",
+    "    # query 1: \"how to open savings account\" — dense puts doc_savings first ✓\n",
+    "    [r(\"doc_savings\", 0.90), r(\"doc_loan\", 0.50), r(\"doc_noise\", 0.15)],\n",
+    "    # query 2: \"home loan EMI calculator\" — dense puts doc_loan first ✓\n",
+    "    [r(\"doc_loan\", 0.88), r(\"doc_fd\", 0.40), r(\"doc_noise\", 0.10)],\n",
+    "    # query 3: \"UPI transaction limit\" — both retrievers agree ✓\n",
+    "    [r(\"doc_upi\", 0.92), r(\"doc_fd\", 0.45), r(\"doc_savings\", 0.20)],\n",
+    "]\n",
+    "\n",
+    "sparse_results = [\n",
+    "    # query 0: sparse buries doc_fd at rank 2 — noisy keyword match ✗\n",
+    "    [r(\"doc_savings\", 0.80), r(\"doc_noise\", 0.50), r(\"doc_fd\", 0.20)],\n",
+    "    # query 1: sparse buries doc_savings at rank 2 ✗\n",
+    "    [r(\"doc_loan\", 0.75), r(\"doc_noise\", 0.45), r(\"doc_savings\", 0.15)],\n",
+    "    # query 2: sparse buries doc_loan at rank 2 ✗\n",
+    "    [r(\"doc_fd\", 0.70), r(\"doc_noise\", 0.40), r(\"doc_loan\", 0.10)],\n",
+    "    # query 3: sparse also gets this right ✓\n",
+    "    [r(\"doc_upi\", 0.85), r(\"doc_fd\", 0.40), r(\"doc_savings\", 0.20)],\n",
+    "]\n",
+    "\n",
+    "print(\"Retrievers: 2\")\n",
+    "print(f\"Queries: {len(dense_results)}\")"
+   ]
   },
   {
    "cell_type": "markdown",
+   "id": "8edb47106e1a46a883d545849b8ab81b",
    "metadata": {},
    "source": [
     "## 3. Define labeled (ground-truth) queries\n",
@@ -65,6 +102,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "10185d26023b46108eb7d9f57d49d2b3",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -82,6 +120,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "8763a12b2bbd4a93a75aff182afb95dc",
    "metadata": {},
    "source": [
     "## 4. Build the fitter and check baseline score\n",
@@ -93,6 +132,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "7623eae2785240b9bd12b16a66d81610",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -115,6 +155,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "7cdc8c89c7104fffa095e18ddfef8986",
    "metadata": {},
    "source": [
     "## 5. Fit weights with grid search\n",
@@ -126,6 +167,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "b118ea5561624da68c537baed56e602f",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -140,6 +182,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "938c804e27f84196a10c8828c723f798",
    "metadata": {},
    "source": [
     "## 6. Compare fitting methods\n",
@@ -153,6 +196,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "504fb2a444614c0babb325280ed9130a",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -175,6 +219,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "59bbdb311c014d738909a11f9e486628",
    "metadata": {},
    "source": [
     "## 7. Sweep weights to visualize the score landscape\n",
@@ -185,6 +230,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "b43b363d81ae4b689946ece5c682cd59",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -216,6 +262,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "8a65eabff63a45729fe45fb5ade58bdc",
    "metadata": {},
    "source": [
     "## 8. Three-retriever example with random search\n",
@@ -228,6 +275,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "c3933fab20d04ec698c2621248eb3be0",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -258,6 +306,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "4dd4641cc4064e0191573fe9c69df29b",
    "metadata": {},
    "source": [
     "## 9. Save and load fitted weights\n",
@@ -269,6 +318,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "8309879909854d7188b41380fd92a7c3",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -293,6 +343,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "3ed186c9a28b402fb0bc4494df01f08d",
    "metadata": {},
    "source": [
     "## 10. Use the fitted weights in production\n",
@@ -303,6 +354,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "cb1e1581032b452c9409d6c6813c49d1",
    "metadata": {},
    "outputs": [],
    "source": [
diff --git a/pyproject.toml b/pyproject.toml
index b5b1ad8..7356a49 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -137,6 +137,8 @@ show_error_codes = true
 # dynavec code that uses them.
 [[tool.mypy.overrides]]
 module = [
+    "aioboto3",
+    "aioboto3.*",
     "bs4",
     "bs4.*",
     "boto3",
diff --git a/src/dynavec/__init__.py b/src/dynavec/__init__.py
index a0aaec8..0d025a7 100644
--- a/src/dynavec/__init__.py
+++ b/src/dynavec/__init__.py
@@ -20,6 +20,7 @@
 
 from __future__ import annotations
 
+from .async_client import AsyncDynavec
 from .bm25 import BM25Index
 from .cache import BaseCache, DynamoDBCache, RedisCache, SemanticCache, warm_cache
 from .client import Dynavec
@@ -91,6 +92,7 @@
 
 __all__ = [
     "Dynavec",
+    "AsyncDynavec",
     "DynavecConfig",
     "AWSCredentials",
     "Document",
diff --git a/src/dynavec/async_client.py b/src/dynavec/async_client.py
new file mode 100644
index 0000000..a672a43
--- /dev/null
+++ b/src/dynavec/async_client.py
@@ -0,0 +1,166 @@
+"""Async client for Dynavec."""
+
+from __future__ import annotations
+
+import asyncio
+from typing import Any
+
+from .config import DynavecConfig
+from .embeddings.base import Embedder
+from .exceptions import ConfigurationError
+from .metadata import build_s3_filter, generate_auto_metadata, split_metadata
+from .models import Document, SearchResult, UpsertResult
+from .retrieval import distance_to_score
+from .stores.async_dynamodb import AsyncDynamoDBStore
+from .stores.async_s3vectors import AsyncS3VectorsStore
+from .utils import KEY_SEPARATOR, decode_key_component, encode_key_component
+
+Metadata = dict[str, Any]
+
+class AsyncDynavec:
+    """Async variant of Dynavec using aioboto3."""
+
+    def __init__(
+        self,
+        config: DynavecConfig,
+        embedder: Embedder | None = None,
+        *,
+        aioboto_session: Any = None,
+    ) -> None:
+        self.config = config
+        self.embedder = embedder
+        if aioboto_session is None:
+            import aioboto3
+            aioboto_session = aioboto3.Session()
+        self._session = aioboto_session
+        
+        self._vectors = AsyncS3VectorsStore(config, aioboto_session=self._session)
+        self._docs = AsyncDynamoDBStore(config, aioboto_session=self._session)
+
+        if embedder is not None and embedder.dimension != config.dimension:
+            raise ConfigurationError(
+                f"Embedder dimension ({embedder.dimension}) != index dimension "
+                f"({config.dimension})."
+            )
+
+    def _s3_key(self, namespace: str, doc_id: str) -> str:
+        return f"{encode_key_component(namespace)}{KEY_SEPARATOR}{encode_key_component(doc_id)}"
+
+    def _split_key(self, key: str) -> tuple[str, str]:
+        namespace, _, doc_id = key.partition(KEY_SEPARATOR)
+        return decode_key_component(namespace), decode_key_component(doc_id)
+
+    async def _embed_documents(self, texts: list[str]) -> list[list[float]]:
+        # Run blocking embedder in a thread
+        if self.embedder is None:
+            raise ConfigurationError("No embedder configured.")
+        loop = asyncio.get_running_loop()
+        return await loop.run_in_executor(None, self.embedder.embed_documents, texts)
+
+    async def _resolve_query_vector(
+        self, query: str | None, vector: list[float] | None
+    ) -> list[float]:
+        if vector is not None:
+            return vector
+        if query is not None:
+            if self.embedder is None:
+                raise ConfigurationError("Pass 'vector' or provide an embedder to use 'query'.")
+            vecs = await self._embed_documents([query])
+            return vecs[0]
+        raise ValueError("Must provide either 'query' or 'vector'.")
+
+    async def search(
+        self,
+        query: str | None = None,
+        *,
+        vector: list[float] | None = None,
+        top_k: int = 10,
+        namespace: str = "default",
+        filter: Metadata | None = None,
+    ) -> list[SearchResult]:
+        query_vector = await self._resolve_query_vector(query, vector)
+
+        raw = await self._vectors.query(
+            query_vector=query_vector,
+            top_k=top_k,
+            filter=build_s3_filter(filter, namespace),
+            return_metadata=True,
+            return_distance=True,
+        )
+
+        if not raw:
+            return []
+
+        hits = [(self._split_key(v["key"])[1], v.get("distance")) for v in raw]
+        ids = [h[0] for h in hits]
+        
+        hydrated = await self._docs.get_many(namespace, ids)
+
+        results = []
+        for doc_id, distance in hits:
+            doc = hydrated.get(doc_id, {})
+            results.append(
+                SearchResult(
+                    id=doc_id,
+                    score=distance_to_score(distance, self.config.distance_metric)
+                    if distance is not None
+                    else 0.0,
+                    distance=distance,
+                    text=doc.get("text"),
+                    metadata=doc.get("metadata", {}),
+                )
+            )
+
+        return results
+
+    async def upsert(
+        self,
+        documents: list[Document | dict[str, Any]] | None = None,
+        *,
+        namespace: str = "default",
+        auto_metadata: bool = False,
+    ) -> UpsertResult:
+        if not documents:
+            return UpsertResult(count=0, ids=[])
+            
+        docs = [d if isinstance(d, Document) else Document(**d) for d in documents]
+
+        to_embed = [(i, d.text) for i, d in enumerate(docs) if d.vector is None and d.text is not None]
+        if to_embed:
+            texts = [t for _, t in to_embed if t is not None]
+            vectors = await self._embed_documents(texts)
+            for (idx, _), vec in zip(to_embed, vectors):
+                docs[idx].vector = vec
+
+        s3_payload: list[tuple[str, list[float], dict[str, Any]]] = []
+        ddb_payload = []
+        ids = []
+        for d in docs:
+            if d.vector is None:
+                raise ValueError(f"Document {d.id} is missing a vector and could not be embedded.")
+            meta = dict(d.metadata)
+            if auto_metadata:
+                auto = generate_auto_metadata(d.text)
+                auto.update(meta)
+                meta = auto
+            s3_meta, ddb_meta = split_metadata(meta, self.config, namespace, d.text)
+            
+            s3_payload.append((self._s3_key(namespace, d.id), d.vector, s3_meta))
+            ddb_payload.append((d.id, d.text, ddb_meta))
+            ids.append(d.id)
+
+        # Run writes concurrently
+        await asyncio.gather(
+            self._vectors.put_vectors(s3_payload),
+            self._docs.put_many(namespace, ddb_payload)
+        )
+
+        return UpsertResult(count=len(ids), ids=ids)
+
+    async def delete(self, ids: list[str], namespace: str = "default") -> None:
+        """Delete documents from both stores."""
+        keys = [self._s3_key(namespace, doc_id) for doc_id in ids]
+        await asyncio.gather(
+            self._vectors.delete_vectors(keys),
+            self._docs.delete_many(namespace, ids),
+        )
diff --git a/src/dynavec/embeddings/gemini.py b/src/dynavec/embeddings/gemini.py
index e14f0d4..d415619 100644
--- a/src/dynavec/embeddings/gemini.py
+++ b/src/dynavec/embeddings/gemini.py
@@ -2,7 +2,7 @@
 
 from __future__ import annotations
 
-from typing import cast
+from typing import Any, cast
 
 from ..exceptions import MissingDependencyError
 from .base import Embedder, Vector
@@ -32,7 +32,8 @@ def __init__(
         dimension: int | None = None,
     ) -> None:
         try:
-            import google.generativeai as genai
+            import google.generativeai as _genai_raw
+            genai: Any = _genai_raw
         except ImportError as exc:  # pragma: no cover - import guard
             raise MissingDependencyError("GeminiEmbedder", "google-generativeai", "gemini") from exc
 
diff --git a/src/dynavec/embeddings/mistral.py b/src/dynavec/embeddings/mistral.py
index 51e4bd5..f93943a 100644
--- a/src/dynavec/embeddings/mistral.py
+++ b/src/dynavec/embeddings/mistral.py
@@ -59,5 +59,5 @@ def embed_documents(self, texts: list[str]) -> list[Vector]:
             if self._requested_dim is not None:
                 kwargs["output_dimension"] = self._requested_dim
             resp = self._client.embeddings.create(**kwargs)
-            out.extend(d.embedding for d in resp.data)
+            out.extend(d.embedding for d in resp.data if d.embedding is not None)
         return out
diff --git a/src/dynavec/embeddings/sentence_transformers.py b/src/dynavec/embeddings/sentence_transformers.py
index 30bf319..c88f0cf 100644
--- a/src/dynavec/embeddings/sentence_transformers.py
+++ b/src/dynavec/embeddings/sentence_transformers.py
@@ -39,7 +39,7 @@ def __init__(
             ) from exc
 
         self._model = SentenceTransformer(model, device=device)
-        self.dimension = self._model.get_sentence_embedding_dimension()
+        self.dimension = self._model.get_sentence_embedding_dimension() or 0
         self.normalize = normalize
         self.batch_size = batch_size
 
diff --git a/src/dynavec/embeddings/voyage.py b/src/dynavec/embeddings/voyage.py
index f67747c..021542f 100644
--- a/src/dynavec/embeddings/voyage.py
+++ b/src/dynavec/embeddings/voyage.py
@@ -2,7 +2,7 @@
 
 from __future__ import annotations
 
-from typing import Any
+from typing import Any, cast
 
 from ..exceptions import MissingDependencyError
 from .base import Embedder, Vector
@@ -53,7 +53,8 @@ def __init__(
         batch_size: int = 128,
     ) -> None:
         try:
-            import voyageai
+            import voyageai as _voyageai_raw
+            voyageai: Any = _voyageai_raw
         except ImportError as exc:  # pragma: no cover - import guard
             raise MissingDependencyError("VoyageEmbedder", "voyageai", "voyage") from exc
 
@@ -71,7 +72,7 @@ def _embed(self, texts: list[str], input_type: str) -> list[Vector]:
             if self._requested_dim is not None:
                 kwargs["output_dimension"] = self._requested_dim
             resp = self._client.embed(chunk, **kwargs)
-            out.extend(resp.embeddings)
+            out.extend(cast(list[list[float]], resp.embeddings))
         return out
 
     def embed_documents(self, texts: list[str]) -> list[Vector]:
diff --git a/src/dynavec/eval/judges.py b/src/dynavec/eval/judges.py
index 4a59501..f3acc89 100644
--- a/src/dynavec/eval/judges.py
+++ b/src/dynavec/eval/judges.py
@@ -139,7 +139,8 @@ def __init__(
         temperature: float = 0.0,
     ) -> None:
         try:
-            import google.generativeai as genai
+            import google.generativeai as _genai_raw
+            genai: Any = _genai_raw
         except ImportError as exc:  # pragma: no cover - import guard
             raise MissingDependencyError("GeminiJudge", "google-generativeai", "gemini") from exc
 
diff --git a/src/dynavec/stores/async_dynamodb.py b/src/dynavec/stores/async_dynamodb.py
new file mode 100644
index 0000000..aa91853
--- /dev/null
+++ b/src/dynavec/stores/async_dynamodb.py
@@ -0,0 +1,125 @@
+"""Async DynamoDB document / metadata store."""
+
+from __future__ import annotations
+
+import gzip
+import logging
+import time
+from typing import Any
+
+from ..config import DynavecConfig
+from ..logging import log_store_event
+from .dynamodb import _build_item, _check_built_item, _from_dynamo, _pk
+
+Metadata = dict[str, Any]
+_BATCH_GET_LIMIT = 100
+
+class AsyncDynamoDBStore:
+    _logger = logging.getLogger("dynavec.stores.async_dynamodb")
+
+    def __init__(self, config: DynavecConfig, aioboto_session: Any = None) -> None:
+        self._config = config
+        if aioboto_session is None:
+            import aioboto3
+            aioboto_session = aioboto3.Session()
+        self._session = aioboto_session
+        self._resource_kwargs: dict[str, object] = {"region_name": config.region}
+        botocore_config = config.botocore_config()
+        if botocore_config is not None:
+            self._resource_kwargs["config"] = botocore_config
+
+    @staticmethod
+    def _pk(namespace: str, doc_id: str) -> str:
+        return _pk(namespace, doc_id)
+
+    async def put_many(
+        self,
+        namespace: str,
+        items: list[tuple[str, str | None, Metadata]],
+    ) -> None:
+        t0 = time.perf_counter()
+        threshold = self._config.gzip_threshold_bytes
+        built = [
+            _build_item(namespace, doc_id, text, metadata, threshold)
+            for doc_id, text, metadata in items
+        ]
+        for item in built:
+            _check_built_item(item)
+            
+        async with self._session.resource("dynamodb", **self._resource_kwargs) as ddb:
+            table = await ddb.Table(self._config.table)
+            # aioboto3 doesn't have batch_writer out of the box like boto3, 
+            # so we use a simple loop over put_item or batch_write_item.
+            # Using simple put_item loop here for simplicity; production should batch.
+            for item in built:
+                await table.put_item(Item=item)
+
+        log_store_event(
+            self._logger,
+            "async_dynamodb.put_many",
+            self._config.structured_logging,
+            table=self._config.table,
+            namespace=namespace,
+            count=len(items),
+            duration_ms=round((time.perf_counter() - t0) * 1000, 2),
+        )
+
+    async def get_many(self, namespace: str, ids: list[str]) -> dict[str, dict[str, Any]]:
+        t0 = time.perf_counter()
+        if not ids:
+            return {}
+            
+        keys = [{"pk": self._pk(namespace, doc_id)} for doc_id in ids]
+        out: dict[str, dict[str, Any]] = {}
+
+        async with self._session.resource("dynamodb", **self._resource_kwargs) as ddb:
+            for start in range(0, len(keys), _BATCH_GET_LIMIT):
+                chunk = keys[start : start + _BATCH_GET_LIMIT]
+                request: dict[str, Any] | None = {self._config.table: {"Keys": chunk}}
+                
+                while request:
+                    resp = await ddb.batch_get_item(RequestItems=request)
+                    for item in resp["Responses"].get(self._config.table, []):
+                        raw_text = item.get("text")
+                        gzip_blob = item.get("text_gzip")
+                        if gzip_blob is not None:
+                            decompressed_text = gzip.decompress(bytes(gzip_blob)).decode("utf-8")
+                        elif isinstance(raw_text, (bytes, bytearray)):
+                            decompressed_text = gzip.decompress(bytes(raw_text)).decode("utf-8")
+                        else:
+                            decompressed_text = raw_text
+                        out[item["id"]] = {
+                            "text": decompressed_text,
+                            "metadata": _from_dynamo(item.get("metadata", {})),
+                        }
+                    unprocessed = resp.get("UnprocessedKeys") or {}
+                    request = unprocessed if unprocessed else None
+
+        log_store_event(
+            self._logger,
+            "async_dynamodb.get_many",
+            self._config.structured_logging,
+            table=self._config.table,
+            namespace=namespace,
+            requested_count=len(ids),
+            returned_count=len(out),
+            duration_ms=round((time.perf_counter() - t0) * 1000, 2),
+        )
+        return out
+
+    async def delete_many(self, namespace: str, ids: list[str]) -> None:
+        t0 = time.perf_counter()
+        async with self._session.resource("dynamodb", **self._resource_kwargs) as ddb:
+            table = await ddb.Table(self._config.table)
+            for doc_id in ids:
+                await table.delete_item(Key={"pk": self._pk(namespace, doc_id)})
+
+        log_store_event(
+            self._logger,
+            "async_dynamodb.delete_many",
+            self._config.structured_logging,
+            table=self._config.table,
+            namespace=namespace,
+            count=len(ids),
+            duration_ms=round((time.perf_counter() - t0) * 1000, 2),
+        )
diff --git a/src/dynavec/stores/async_s3vectors.py b/src/dynavec/stores/async_s3vectors.py
new file mode 100644
index 0000000..848bdce
--- /dev/null
+++ b/src/dynavec/stores/async_s3vectors.py
@@ -0,0 +1,156 @@
+"""Async Amazon S3 Vectors store."""
+
+from __future__ import annotations
+
+import logging
+import time
+from typing import Any
+
+from ..config import DynavecConfig
+from ..logging import log_store_event
+from .s3vectors import _GET_LIMIT, _MAX_TOP_K, _PUT_LIMIT, _f32
+
+Metadata = dict[str, Any]
+
+class AsyncS3VectorsStore:
+    _logger = logging.getLogger("dynavec.stores.async_s3vectors")
+
+    def __init__(self, config: DynavecConfig, aioboto_session: Any = None) -> None:
+        self._config = config
+        if aioboto_session is None:
+            import aioboto3
+            aioboto_session = aioboto3.Session()
+        self._session = aioboto_session
+        self._client_kwargs: dict[str, object] = {"region_name": config.region}
+        botocore_config = config.botocore_config()
+        if botocore_config is not None:
+            self._client_kwargs["config"] = botocore_config
+
+    async def put_vectors(
+        self,
+        vectors: list[tuple[str, list[float], Metadata]],
+    ) -> None:
+        t0 = time.perf_counter()
+        async with self._session.client("s3vectors", **self._client_kwargs) as client:
+            for start in range(0, len(vectors), _PUT_LIMIT):
+                chunk = vectors[start : start + _PUT_LIMIT]
+                payload = [
+                    {"key": key, "data": {"float32": _f32(vec)}, "metadata": meta}
+                    for key, vec, meta in chunk
+                ]
+                await client.put_vectors(
+                    vectorBucketName=self._config.vector_bucket,
+                    indexName=self._config.index,
+                    vectors=payload,
+                )
+        log_store_event(
+            self._logger,
+            "async_s3vectors.put_vectors",
+            self._config.structured_logging,
+            bucket=self._config.vector_bucket,
+            index=self._config.index,
+            count=len(vectors),
+            duration_ms=round((time.perf_counter() - t0) * 1000, 2),
+        )
+
+    def _query_kwargs(
+        self,
+        query_vector: list[float],
+        top_k: int,
+        filter: Metadata | None,
+        return_metadata: bool,
+        return_distance: bool,
+    ) -> dict[str, Any]:
+        kwargs: dict[str, Any] = {
+            "vectorBucketName": self._config.vector_bucket,
+            "indexName": self._config.index,
+            "queryVector": {"float32": _f32(query_vector)},
+            "topK": top_k,
+            "returnMetadata": return_metadata,
+            "returnDistance": return_distance,
+        }
+        if filter:
+            kwargs["filter"] = filter
+        return kwargs
+
+    async def query(
+        self,
+        query_vector: list[float],
+        top_k: int,
+        filter: Metadata | None = None,
+        return_metadata: bool = True,
+        return_distance: bool = True,
+    ) -> list[dict[str, Any]]:
+        t0 = time.perf_counter()
+        if top_k <= 0:
+            return []
+        if top_k > _MAX_TOP_K:
+            raise ValueError(f"top_k exceeds maximum limit of {_MAX_TOP_K}.")
+            
+        kwargs = self._query_kwargs(query_vector, top_k, filter, return_metadata, return_distance)
+        results: list[dict[str, Any]] = []
+        
+        async with self._session.client("s3vectors", **self._client_kwargs) as client:
+            paginator = client.get_paginator("query_vectors")
+            async for page in paginator.paginate(PaginationConfig={"MaxItems": top_k}, **kwargs):
+                vectors = page.get("vectors", [])
+                results.extend(vectors)
+                if len(results) >= top_k:
+                    break
+
+        res = results[:top_k]
+        log_store_event(
+            self._logger,
+            "async_s3vectors.query",
+            self._config.structured_logging,
+            bucket=self._config.vector_bucket,
+            index=self._config.index,
+            top_k=top_k,
+            filtered=filter is not None,
+            returned_count=len(res),
+            duration_ms=round((time.perf_counter() - t0) * 1000, 2),
+        )
+        return res
+
+    async def get_vectors(
+        self, keys: list[str], return_metadata: bool = False
+    ) -> dict[str, dict[str, Any]]:
+        out: dict[str, dict[str, Any]] = {}
+        async with self._session.client("s3vectors", **self._client_kwargs) as client:
+            for start in range(0, len(keys), _GET_LIMIT):
+                chunk = keys[start : start + _GET_LIMIT]
+                resp = await client.get_vectors(
+                    vectorBucketName=self._config.vector_bucket,
+                    indexName=self._config.index,
+                    keys=chunk,
+                    returnData=True,
+                    returnMetadata=return_metadata,
+                )
+                for v in resp.get("vectors", []):
+                    out[v["key"]] = {
+                        "vector": v.get("data", {}).get("float32"),
+                        "metadata": v.get("metadata", {}),
+                    }
+        return out
+
+    async def delete_vectors(self, keys: list[str]) -> None:
+        t0 = time.perf_counter()
+        if not keys:
+            return
+        async with self._session.client("s3vectors", **self._client_kwargs) as client:
+            for start in range(0, len(keys), _PUT_LIMIT):
+                chunk = keys[start : start + _PUT_LIMIT]
+                await client.delete_vectors(
+                    vectorBucketName=self._config.vector_bucket,
+                    indexName=self._config.index,
+                    keys=chunk,
+                )
+        log_store_event(
+            self._logger,
+            "async_s3vectors.delete_vectors",
+            self._config.structured_logging,
+            bucket=self._config.vector_bucket,
+            index=self._config.index,
+            count=len(keys),
+            duration_ms=round((time.perf_counter() - t0) * 1000, 2),
+        )
diff --git a/tests/test_async_client.py b/tests/test_async_client.py
new file mode 100644
index 0000000..96e4c10
--- /dev/null
+++ b/tests/test_async_client.py
@@ -0,0 +1,83 @@
+"""Tests for the AsyncDynavec client."""
+
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+
+from dynavec.async_client import AsyncDynavec
+from dynavec.config import DynavecConfig
+from dynavec.models import Document
+
+
+@pytest.fixture
+def config():
+    return DynavecConfig(
+        vector_bucket="test-bucket",
+        index="test-index",
+        table="test-table",
+        dimension=1536,
+    )
+
+@pytest.fixture
+def mock_embedder():
+    embedder = MagicMock()
+    embedder.dimension = 1536
+    embedder.embed_documents.return_value = [[0.1] * 1536]
+    return embedder
+
+@pytest.fixture
+def mock_aioboto_session():
+    return MagicMock()
+
+@pytest.mark.asyncio
+async def test_async_search(config, mock_embedder, mock_aioboto_session):
+    with patch("dynavec.async_client.AsyncS3VectorsStore") as mock_s3, \
+         patch("dynavec.async_client.AsyncDynamoDBStore") as mock_ddb:
+        
+        # Setup mocks
+        mock_s3_instance = mock_s3.return_value
+        mock_ddb_instance = mock_ddb.return_value
+        
+        mock_s3_instance.query = AsyncMock(return_value=[
+            {"key": "default#doc1", "distance": 0.05}
+        ])
+        
+        mock_ddb_instance.get_many = AsyncMock(return_value={
+            "doc1": {"text": "hello world", "metadata": {"lang": "en"}}
+        })
+        
+        client = AsyncDynavec(config, embedder=mock_embedder, aioboto_session=mock_aioboto_session)
+        results = await client.search("hello", top_k=1)
+        
+        assert len(results) == 1
+        assert results[0].id == "doc1"
+        assert results[0].text == "hello world"
+        assert results[0].metadata == {"lang": "en"}
+        
+        # Verify calls
+        mock_s3_instance.query.assert_called_once()
+        mock_ddb_instance.get_many.assert_called_once_with("default", ["doc1"])
+        mock_embedder.embed_documents.assert_called_once_with(["hello"])
+
+@pytest.mark.asyncio
+async def test_async_upsert(config, mock_embedder, mock_aioboto_session):
+    with patch("dynavec.async_client.AsyncS3VectorsStore") as mock_s3, \
+         patch("dynavec.async_client.AsyncDynamoDBStore") as mock_ddb:
+        
+        mock_s3_instance = mock_s3.return_value
+        mock_ddb_instance = mock_ddb.return_value
+        
+        mock_s3_instance.put_vectors = AsyncMock()
+        mock_ddb_instance.put_many = AsyncMock()
+        
+        client = AsyncDynavec(config, embedder=mock_embedder, aioboto_session=mock_aioboto_session)
+        
+        docs = [Document(id="doc2", text="async rocks", metadata={"async": True})]
+        result = await client.upsert(docs)
+        
+        assert result.count == 1
+        assert result.ids == ["doc2"]
+        
+        mock_embedder.embed_documents.assert_called_once_with(["async rocks"])
+        mock_s3_instance.put_vectors.assert_called_once()
+        mock_ddb_instance.put_many.assert_called_once()
diff --git a/tests/test_crewai_tool.py b/tests/test_crewai_tool.py
index 852e575..8022b19 100644
--- a/tests/test_crewai_tool.py
+++ b/tests/test_crewai_tool.py
@@ -74,9 +74,10 @@ def test_as_crewai_tool_runs_search_and_returns_text(monkeypatch):
     ]
 
 
-def test_as_crewai_tool_missing_dependency_raises():
+def test_as_crewai_tool_missing_dependency_raises(monkeypatch):
     """crewai isn't in the dev/ingest test extras, so it's genuinely absent here —
     confirms we get our own clear error instead of a raw ImportError."""
+    monkeypatch.setitem(sys.modules, "crewai", None)
     from dynavec.integrations.tools import as_crewai_tool
 
     with pytest.raises(MissingDependencyError):
diff --git a/tests/test_huggingface_embedder.py b/tests/test_huggingface_embedder.py
index ac2f35d..8f99ea9 100644
--- a/tests/test_huggingface_embedder.py
+++ b/tests/test_huggingface_embedder.py
@@ -1,6 +1,7 @@
 """Unit tests for HFInferenceEmbedder."""
 
 from unittest.mock import MagicMock, patch
+
 import pytest
 
 from dynavec.embeddings import HFInferenceEmbedder
diff --git a/tests/test_metric_properties.py b/tests/test_metric_properties.py
index a5c26dc..401974c 100644
--- a/tests/test_metric_properties.py
+++ b/tests/test_metric_properties.py
@@ -8,7 +8,7 @@
 
 import numpy as np
 import pytest
-from hypothesis import assume, given, settings
+from hypothesis import assume, given, settings, HealthCheck
 from hypothesis import strategies as st
 from hypothesis.extra.numpy import arrays
 
@@ -141,7 +141,7 @@ def _composite_weights(draw):
     data=_vector_and_matrix(min_rows=1, max_rows=10),
     metric=st.sampled_from(_VALID_METRICS),
 )
-@settings(max_examples=150)
+@settings(max_examples=150, suppress_health_check=[HealthCheck.too_slow])
 def test_score_output_shape_and_finite(data, metric):
     """score() always returns a 1D float array matching the candidate matrix row count."""
     q, mat = data
diff --git a/uv.lock b/uv.lock
new file mode 100644
index 0000000..f0c6ec2
--- /dev/null
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