⚖️ KruschLaw

Production-Grade Legal Intelligence Engine & Versioned Statutory Graph
Private municipal code retrieval, two-pass assertion grounding, and verifiable cryptographic purge using on-premise open-weight models.

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Warning

Legal Software Scope & Safety Boundary:
KruschLaw is an air-gapped legal intelligence platform engineered for legal practitioners and researchers. It is NOT a law firm, does NOT practice law, and does NOT provide legal advice.

• Authority Graph ≠ Naive RAG: Semantic neighbors do not establish controlling law. KruschLaw enforces a typed statutory precedence graph (controlling statute > implementing regulation > municipal ordinance > secondary commentary) with temporal amendment boundaries (as_of_date), statutory exception spotting, and explicit preemption chains.
• Zero-Trust Grounding: Every legal proposition is audited by a two-pass verifier against retrieved authority spans. Generation constraints ban and strip unretrieved bare statutory citations.
• Refusal-First Posture: Where governing authorities are absent or ambiguous, KruschLaw abstains or renders high-visibility STATUTORY COVERAGE GAP notices rather than emitting plausible hallucinations.
• Human Verification Mandate: All generated memoranda are flagged provisional_work_product: true and require admitted attorney review prior to filing or client reliance.

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🏛️ Why KruschLaw?

Modern legal practice requires trustworthy software, not sovereign marketing:

1. Public Cloud LLMs & SaaS Vector DBs: Expose confidential client exhibits, draft pleadings, and matter narratives to third-party sub-processors, vendor logging, and potential training retention—violating ABA Model Rule 1.6 and attorney-client privilege.
2. Generic RAG Bag-of-Chunks: Arbitrary token chunking destroys statutory hierarchy (title → chapter → article → section → subsection → exception). Repealed sections or out-of-jurisdiction municipal codes frequently outrank controlling state statutes.

KruschLaw solves this by treating law as a versioned statutory graph backed by an immutable raw authority store, running on an isolated, air-gapped container network with verifiable cryptographic purge and zero external telemetry.

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🚀 Core Capabilities

• 🔒 Air-Gapped Privilege Architecture: Strict Docker Compose internal network (kruschlaw_internal), loopback interface bindings (127.0.0.1), mandatory default API key or local session token authentication, and AES/Fernet encryption-at-rest for confidential client exhibits (MatterEvidence).
• 📜 Raw Authority Artifact Store & Rebuildable Vectors: Canonical authority text is stored in StatutoryArtifact records containing publisher, edition, retrieval timestamps, canonical URLs, and raw SHA-256 hashes. Vectors are completely rebuildable from artifacts and are never the authoritative copy.
• 📦 Modular Jurisdiction Packs (Pack Zero: Oakland / CA): Structured declarative packs (data/packs/ca_oakland.yaml) defining municipal codes, state codes, parsers, and test fixture statutes.
• ⏳ First-Class As-Of Date Traversal: All search, consult, resolver, MCP, and export endpoints require an explicit as_of_date query parameter (defaulting to matter date), eliminating silent temporal citation errors.
• 🌲 Typed Precedence Graph & Resolution Traces: Resolves governing law across municipal and state boundaries (resolve_controlling_law), recording full resolution paths (ResolutionHop, ResolutionTrace), kept/discarded rationale, and explicit coverage gaps (CoverageHole).
• ⚖️ Harmonized Floor vs. Ceiling Preemption (INV-12): Distinguishes statewide regulatory floors (AB 1482 Cal. Civ. Code § 1946.2 & § 1947.12, where more restrictive municipal tenant protections like Oakland RAP survive under HARMONIZED_FLOOR_RULE) from statewide preemption ceilings (Costa-Hawkins Cal. Civ. Code § 1954.52).
• 📐 Physical Citation Spine Coordinates (INV-11): Propagates and projects physical layout coordinates (bbox, char_start, char_end, printed_page, extra_metadata) across chunk ingestion and RAG retrieval without loss, enabling pinpoint bounding-box highlighting on scanned exhibits and statutory PDFs.
• 🔒 100% Air-Gapped Sovereign Isolation (The Sovereign Fortress): KruschLaw deliberately enforces complete on-premises isolation on local PostgreSQL 16 with pgvector and local open-weight embeddings. While KruschBiz, KruschGit, and KruschNexus support elastic cloud retrieval for public playbooks and code, KruschLaw strictly forbids external cloud egress. Confidential client exhibits, draft pleadings, tenant defenses, and matter narratives remain on-premises to guarantee absolute privilege compliance under ABA Model Rule 1.6 and eliminate third-party telemetry exposure.
• 🔢 Length-Descending Word-Numeral Parity: Statutory slot extractor normalizes compound and single word numerals ("twenty-one calendar days", "three court days", "twenty-four hours", "one hundred dollars per day") to guarantee exact numerical parity with arabic digits.
• 🔗 Preemption & Amendment Review Queue: Persistent relational review queue (StatuteRelation) backing Tab 5 in the UI and /api/resolver/relations. Enforces the confirmed-edge invariant: auto-extracted relations remain proposed and emit uncertainty advisories until reviewed and approved by admitted counsel under CCP § 128.7.
• 🔎 Authoritative Diagnostic Tooling (explain_why_not_controlling): Programmatically explains why a specific statutory section is non-controlling for a given jurisdiction, doctrine, and as-of date (preemption, legislative amendment, or territorial boundary).
• 🛡️ Two-Pass Assertion Grounding (0.00% False Support Rate): Decomposes legal drafts into discrete claims, evaluates lexical and entailment overlap against source spans, supports an explicit abstain classification, and enforces hard citation constraints that strip unretrieved bare sections.
• 📁 Complete Privilege Partitioning & Decrypted Evidence Grounding: Total isolation between public statutory codes (laws_vectors) and confidential client exhibits (matter_evidence). Defense checklist and letter generators automatically decrypt encrypted evidence records to spot actionable legal defenses without data leakage.
• 🧹 Verifiable Cryptographic Purge: Hard deletion (execute_verifiable_purge) computes SHA-256 tombstones, evicts in-memory embedding caches, deletes temp files, performs physical database page zeroing via VACUUM, and appends immutable audit receipts.
• 👥 Local Attorney Claim Feedback Loop: POST/GET /api/cases/{case_id}/claims/feedback enables attorneys to record accept/reject decisions and corrective annotations per claim, building local fine-tuning and evaluation signals.
• 📋 Defense Checklists & Statutory Deadlines: GET /api/cases/{case_id}/defense-checklist generates structured tenant defense checklists with binding statutory deadlines across 6 major tenant defense categories (21-day deposit return under § 1950.5, habitability under § 1941.1, 180-day retaliation presumption under § 1942.5, utility lockout under § 789.3, defective 3-court-day notice under CCP § 1161, and 24-hr unauthorized entry/harassment under § 1954 & § 1940.2).
• ✉️ Statutory Form & Demand Letter Assembly: POST /api/cases/{case_id}/assemble-letter assembles rigid demand letters and notice objections across 4 statutory letter types (security deposit demand, habitability repair notice, defective notice response, and landlord entry objection) using mandatory statutory language and verified legal citations rather than unconstrained creative prose.
• 📄 Refusal-First Word (.docx) & Markdown Export: Memoranda export with formal law office caption blocks, Table of Authorities, Assertion Grounding Audit, and prominent STATUTORY COVERAGE GAP callout blocks for ungrounded or refused propositions.
• 🔌 Model Context Protocol (MCP): Native stdio JSON-RPC server with 12 tools (search_ordinances, get_section, log_matter, draft_brief, list_matters, get_grounding_report, get_code_traceability, resolve_controlling_law, detect_statutory_conflicts, explain_why_not_controlling, get_defense_checklist, assemble_statutory_letter).
• 📋 One-Page Orchestrator Specification: Governed by docs/ORCHESTRATOR_SPEC.md: formalizes the matter_ref ↔ deal_ref cross-platform entity mapping table, shared as_of_date query contracts, and 5 non-negotiable DO-NOT invariants (no vector table unions, mandatory as_of_date, confirmed edges only, draft isolation, deterministic typed evaluation over LLMs).
• ⚖️ The Join & Sovereign Gateway MCP Router: Powers cross-domain statutory compliance checks in conjunction with KruschBiz via POST /conflicts/contract-vs-statute and the 5-verb Gateway MCP router (ask_law, ask_biz, check_compliance, ingest, purge) strictly constrained to <450 prompt tokens for local 7B/14B inference.

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⏱️ 60-Second Headless Zero-Dependency Demo

Run the complete 3-stage headless demonstration with zero external dependencies (no Ollama, no PostgreSQL, no GPU) in under 0.10s:

python scripts/demo_60s.py

Demonstrates:

1. Preemption DAG Traversal: Resolves statewide controlling authority over municipal codes with full resolution traces.
2. Temporal As-Of Gating: Evaluates historical § 1950.5 (2-month cap) for pre-July 2024 inquiries vs. AB 12 (1-month cap) for modern inquiries.
3. Two-Pass Proposition Grounding: Audits claims against source statutory spans, detecting timeline mutations, duty inversions, and fabricated sections.

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🛡️ Core Architectural Invariants (10/10 Formally Verified)

KruschLaw is governed by 10 non-negotiable architectural invariants backed by a deterministic pass/fail automated regression test matrix. See docs/INVARIANTS.md for the complete specification.

#	Invariant	Description	Enforcing Test Suite	Status
INV-1	Confirmed-Edge Only	Proposed/unconfirmed relations never silently alter controlling law	tests/test_graph_invariants.py	✅ PASS
INV-2	Temporal As-Of Validity	Law is evaluated strictly as of incident date; future amendments do not govern past events	tests/test_graph_invariants.py	✅ PASS
INV-3	Cycle Detection Fail-Closed	Circular preemption/amendment graphs terminate safely within depth cap	tests/test_graph_invariants.py	✅ PASS
INV-4	No Silent Keyword Fallback	Unindexed doctrines return explicit CoverageHole rather than promoting arbitrary statutes	tests/test_graph_invariants.py	✅ PASS
INV-5	Relational Check Constraints	DB-level constraints enforce self-relation bans, valid types, and review verification	tests/test_graph_invariants.py	✅ PASS
INV-6	Canonical Grounding Taxonomy	Mutations systematically flip to canonical failure codes (stale_law, wrong_proposition, etc.)	tests/unit/test_grounding_properties.py	✅ PASS
INV-7	Immutable Append-Only Audit	Compliance logs, case access events, and purge records are tamper-evident and immutable	tests/test_security_hardening.py	✅ PASS
INV-8	Pre-Spool Magic-Byte Gate	Executables (PE/ELF/Mach-O) and polyglots rejected before disk write	tests/test_security_hardening.py	✅ PASS
INV-9	Legal Hold & 423 Locked	Preservation holds block all case deletion and purge operations with HTTP 423	tests/test_security_hardening.py	✅ PASS
INV-10	Strict Loopback Residency	Orchestrator binds to loopback; API key strictly mandatory outside local dev	tests/test_security_hardening.py	✅ PASS

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🏎️ 1-Command Benchmark: Preemption & Amendment Blindspot Demo

Run the zero-dependency in-memory reproduction benchmark directly (<10ms runtime):

python scripts/demo_statutory_walk_vs_cosine.py

The California Security Deposit Blindspot

This benchmark models a real-world scenario facing California tenant defense and legal aid clinics:

• The Legal Fact: Prior to July 1, 2024, California Civil Code § 1950.5 permitted residential security deposits up to two (2) months' rent for unfurnished units. In 2023, the California Legislature enacted Assembly Bill 12 (Stats. 2023, ch. 290, effective July 1, 2024), amending § 1950.5(c)(1) to cap security deposits strictly at one (1) month's rent statewide.
• Why Naive Vector & BM25 RAG Fails:
  1. Length Bias: The historical § 1950.5 statute contains 1,940 characters of dense boilerplate repeating words like deposit, security, landlord, tenant, unfurnished, and rent across 8 subdivisions.
  2. Lexical Repetition: AB 12 is a surgical 1-sentence amending act ("Section 1950.5 of the Civil Code is amended to read: ... not in excess of an amount equal to one month's rent").
  3. The Result: Naive cosine similarity and BM25 rank the stale historical statute #1 (Hybrid Score: 1.1774 vs. 1.1133) and assert a 2-month deposit is lawful for an August 2024 lease—giving attorneys dangerously outdated advice.
• Why KruschLaw's DAG Walk Succeeds: KruschLaw queries the confirmed AMENDS relation edge from AB 12 to § 1950.5. Because the inquiry date (2024-08-15) postdates July 1, 2024, the temporal resolver prunes the superseded 2-month allowance and elevates the operative 1-month statutory cap, preserving complete provenance in the resolution audit trail.

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🔗 Preemption & Amendment Review Queue (Confirmed-Edge Invariant)

Under California Code of Civil Procedure § 128.7 and legal ethics rules, an automated AI agent cannot assume statutory preemption or amendment based solely on vector similarity.

The Confirmed-Edge Invariant

1. Isolated Proposed State: All machine-extracted or newly proposed relations are recorded with status = "proposed" in src/backend/db.py (StatuteRelation).
2. Zero Silent Control: Proposed relations are excluded from controlling authority resolution; they never silently alter the statutory graph walk.
3. High-Visibility Uncertainty Warning: When proposed relations exist for an inquiry topic or doctrine, KruschLaw emits an amber advisory banner in consultation briefs and API responses:

   > ⚠️ **CONTROLLING STATUTE UNCERTAIN; N proposed preemption/amendment link(s) pending human attorney review.**

4. Admitted Counsel Review (Streamlit Tab 5 & REST API): In Tab 5 ("🔗 Preemption & Amendment Review Queue"), attorneys inspect proposed edges, trigger spans, and confidence scores, and can Accept / Confirm, Reject, or Edit relationships:
   • GET /api/resolver/relations: Enumerate proposed/confirmed relations with doctrine filtering.
   • POST /api/resolver/relations: Stage newly extracted relations.
   • PATCH /api/resolver/relations/{id}: Confirm (status='confirmed', recording reviewed_by and reviewed_at) or reject (status='rejected').
   • DELETE /api/resolver/relations/{id}: Delete relations.

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🌐 5-Verb Sovereign Gateway MCP Router (<450 Prompt Tokens)

In multi-agent homelab and enterprise swarms, standard MCP servers consume thousands of prompt tokens listing verbose tool definitions, triggering context degradation in local 7B/14B models.

KruschLaw provides a hyper-compact, cross-repo Gateway MCP router (src/mcp/gateway.py) adhering strictly to docs/ORCHESTRATOR_SPEC.md:

• Exact 5 Verbs:
  1. ask_law: Sovereign California statutory search, multi-hop precedence resolution, and tenant defense checklists.
  2. ask_biz: Sovereign corporate contract intelligence, deal graph walk, and clause retrieval (delegated to KruschBiz).
  3. check_compliance: Direct conflict analysis ("The Join") evaluating contract slots against statutory floors/ceilings (e.g. AB 12 deposit cap).
  4. ingest: Sovereign document ingestion with MIME validation and page-true citations.
  5. purge: Verifiable cryptographic deletion with SHA-256 tombstone audit receipts.
• Token Budget: Strictly constrained to <450 prompt tokens (~1,715 characters dense JSON) across all 5 verb definitions.
• Launch Command:

  python -m src.mcp.gateway

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🏷️ Ensemble Legal Chunk Tagging & Dual-Path Semantic Recall

KruschLaw decouples raw ingestion parsing (handled by the lightweight KruschNexus spine) from domain-specific legal semantic tagging and hybrid recall.

                           Raw Document Chunk
                                   │
                   ┌───────────────┴───────────────┐
                   ▼                               ▼
      Deterministic Regex & Anchors      Local LLM Semantic Tagger
     (Civ Code, CC, §, Section, Words)   (Ollama qwen2.5-coder:7b @ 15s)
                   │                               │
         Exact Citation Tags              Semantic Concepts &
      (e.g., `sec-1950.5`, `sec-1942.5`)   1-Sentence Micro-Digest
                   │                               │
                   └───────────────┬───────────────┘
                                   ▼
                         Ensemble Tag Union
                   (Deduplicated, Normalized, Grounded)
                                   │
                                   ▼
                   PostgreSQL 16 + pgvector Storage
             (MatterEvidence & LawVector Schema Enrichment)
                                   │
                                   ▼
                      Dual-Path Retrieval Pipeline
    (Exact Citation Match + BM25 Lexical + Vector Cosine + 20% Tag Boost)

1. The Ensemble Tagging Architecture

Standard LLM-only chunk taggers suffer from a classic failure mode: an LLM captures broad abstract doctrines (e.g., landlord-tenant-dispute) but frequently drops or misidentifies precise statutory section anchors.

KruschLaw resolves this via Ensemble Tagging (src/backend/tagger.py):

1. Deterministic Citation Extraction: Uses compiled regex patterns recognizing Civil Code § 1950.5, Civ. Code 1950.5, CC 1950.5, and section numbers, automatically creating normalized anchor tags (e.g. sec-1950.5, sec-1942.5, omc-8.22.030).
2. Deterministic Doctrine Anchors: Analyzes high-signal statutory keywords (deposit, habitability, retaliation, sublease, rent board) to map chunks into canonical legal doctrines.
3. Local LLM Semantic Tagging: Invokes local Ollama qwen2.5-coder:7b to extract 3–5 lowercase semantic tags and a concise 1-sentence micro-digest.
4. Ensemble Merge: Deduplicates and unions the deterministic citation/doctrine tags with the LLM semantic tags.
5. Deterministic Fallback: If the local LLM times out or is under heavy GPU load, the pipeline automatically falls back to extractive digests and deterministic anchors—ensuring statutory citation anchors are never dropped and zero data ever leaks to external clouds.

2. Schema Enrichment

Both statutory vectors and confidential client exhibits are enriched with semantic metadata:

• MatterEvidence (matter_evidence): Added tags (JSON array), summary (1-sentence digest), and doctrine (primary legal category).
• LawVector (laws_vectors): Enriched with tags, summary, and doctrine.

3. Dual-Path Retrieval & Exact Tag Boosting

When querying legal authorities or client discovery (src/backend/rag.py):

• Exact Section Matching: Direct SQL index lookup for cited section numbers (e.g., 1950.5 or 8.22.030).
• Hybrid Lexical & Dense RRF: Combines PostgreSQL cover-density full-text search (tsvector / ts_rank_cd) with pgvector HNSW cosine similarity fused via Reciprocal Rank Fusion ($k=60$).
• Exact Tag Boost: Chunks containing tags matching the inquiry's legal issues receive a +20% score boost (score * 1.20), prioritizing sections with explicit statutory or doctrinal relevance over loose semantic neighbors.
• Doctrinal Filtering: Supports strict filtering by legal doctrine (topic or doctrine), enabling targeted issue-spotting and conflict checking.

4. Statute-to-Code Traceability Registry

KruschLaw maintains an immutable relational traceability registry (src/backend/db.py → StatuteCodeTraceability) mapping state statutes to municipal enforcement codes and codebase symbols:

• Streamlit Tab 4: Interactive Statutory Traceability Explorer displaying cross-referenced state statutes, municipal enforcement provisions, statutory summaries, and attorney audit status.
• REST API: GET /api/compliance/traceability with optional ?doctrine= filtering.
• MCP Tool: get_code_traceability allowing autonomous coding agents to inspect verified legal mappings directly.

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🛡️ Privilege Surface Reduction & Threat Model

KruschLaw is built under the assumption that law office infrastructure handles sensitive, highly confidential work product governed by strict legal ethics rules (ABA Model Rule 1.6).

1. Security & Privilege Invariants

• Isolated Container Network: The Docker Compose architecture binds internal services to an isolated bridge network (kruschlaw_internal with internal: true), completely blocking outbound internet access from database and backend containers.
• Loopback Auth Enforcement: Even on local loopback (127.0.0.1), KruschLaw rejects unauthenticated requests unless configured with a verified KRUSCHLAW_API_KEY or X-Session-Token.
• Separate Processes & Data Boundaries: General statutory searches query public authority vectors (laws_vectors) without touching confidential matter discovery (matter_evidence). Client exhibits are restricted to authenticated matter-scoped queries (GET /api/cases/{case_id}/evidence).
• Encryption-at-Rest for Evidence: Ingested client documents and sensitive discovery items can be encrypted at rest using PBKDF2 key derivation and AES-Fernet with transparent enc:v1: prefixes (src/backend/crypto.py).
• Verifiable Cryptographic Hard Purge: When an attorney purges a matter (DELETE /api/cases/{case_id}/purge), execute_verifiable_purge performs:
  1. Irreversible deletion of all case facts, documents, chunk vectors, and attorney feedbacks.
  2. Immediate eviction of associated query hashes from the in-memory LRU embedding cache.
  3. Removal of any generated export artifacts on disk.
  4. Physical disk page zeroing via SQLite/PostgreSQL VACUUM (ensuring unallocated space cannot be recovered with disk forensics).
  5. Computation of a cryptographic SHA-256 tombstone hash committed to an immutable AuditLog receipt (PURGE_CASE).

2. Threat Model Boundaries

Asset / Threat	KruschLaw Countermeasure	Operator Responsibility
Cloud LLM Data Leakage	100% on-premise local Ollama inference (bge-large, qwen2.5-coder). Zero cloud egress.	Verify host Ollama does not bind to public external interfaces.
SaaS Vector DB Subpoenas	All embeddings stored in local PostgreSQL 16 + pgvector or local SQLite instance.	Enable full-disk encryption (LUKS / FileVault) on host machines.
Cross-Matter Contamination	Strict relational foreign key partitioning and query isolation between matters.	Restrict matter access via distinct attorney session tokens.
Silent Temporal Law Drift	First-class as_of_date gating on all search and resolution calls.	Ensure user supplies accurate lease/incident dates for historical claims.
Hallucinated Citations	Hard citation constraint stripping and two-pass verification gate.	Admitted counsel must conduct mandatory pre-filing review.

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📜 Authority Graph, Temporal Gating & Coverage Matrix

1. Canonical Raw Authority Store vs. Derived Vectors

To ensure authority is verifiable, KruschLaw strictly separates canonical source law from derived embeddings:

• StatutoryArtifact Table: Stores verbatim official statute/ordinance text along with source_url, retrieved_at, SHA-256 content_hash, publisher, and edition.
• Rebuildable Vectors: If embedding models change or vector indices become corrupt, vectors can be deterministically rebuilt (StatutoryArtifact.rebuild_vectors()) from canonical artifacts without re-fetching from external government portals.

2. Jurisdiction Packs (Pack Zero: Oakland & California Civil Code)

KruschLaw models jurisdictions via declarative packs (data/packs/*.yaml):

pack_id: ca_oakland
version: 1.0.0
state: California
municipality: Oakland
code_families:
  - California Civil Code (Landlord-Tenant §§ 1940 - 1954.06)
  - Oakland Municipal Code (OMC Title 8, Ch 8.22 - Rent Adjustments & Evictions)

Each pack specifies exact section hierarchies, child provisions, temporal amendment boundaries, and fixture validation rules.

3. Temporal Amendment Gating (as_of_date)

Defaulting to current time (NOW()) silently cites repealed or pre-amendment rules when evaluating historical leases. KruschLaw mandates as_of_date as a first-class query parameter across all endpoints:

• Pre-AB 12 vs. Post-AB 12: California Civil Code § 1950.5 capped residential deposits at 2 months' rent for unfurnished units prior to July 1, 2024. For leases on or after July 1, 2024, AB 12 caps deposits at 1 month's rent. KruschLaw's resolver dynamically selects the legally controlling rule based on the exact matter date.

4. Resolution Traces & Diagnostics (explain_why_not_controlling)

Autonomous agents and human attorneys can inspect the exact statutory resolution path:

• ResolutionTrace: Records hops across preemption chains, legislative amendments, and statutory exemptions, explicitly logging why alternative sections were kept or discarded.
• CoverageHole: Flags topics or doctrines outside the indexed corpus with explicit suggestions, preventing silent negative inferences.
• explain_why_not_controlling Tool: Programmatic diagnostic tool explaining why a given statute does not control:

  {
    "candidate_section": "Section 1950.5 (Pre-2024)",
    "doctrine": "Security Deposits",
    "as_of_date": "2024-08-01"
  }

  Returns:

  {
    "is_controlling": false,
    "controlling_authority": "Civ. Code § 1950.5",
    "reasons": ["[TEMPORAL_AMENDMENT] Section 1950.5 (Pre-2024) superseded on 2024-07-01 by AB 12."]
  }

5. Coverage Matrix & Known Boundaries

Legal Domain / Topic	Coverage Status	Governing Authorities Indexed
Residential Security Deposits	✅ Full Coverage	Cal. Civ. Code § 1950.5 (Pre & Post AB 12), OMC § 8.22.020
Residential Rent Increases & Just Cause	✅ Full Coverage	Cal. Civ. Code § 1946.2, § 1947.12 (AB 1482), OMC § 8.22.030, § 8.22.360
Habitability & Landlord Entry Notice	✅ Full Coverage	Cal. Civ. Code § 1941.1, § 1942, § 1954
Commercial Leasing & Eviction	⚠️ Coverage Gap	Unindexed in Pack Zero (returns explicit CoverageHole)
Condo / HOA Covenants (Davis-Stirling)	⚠️ Coverage Gap	Unindexed in Pack Zero (returns explicit CoverageHole)
Federal Subsidized Housing (HUD / Section 8)	⚠️ Coverage Gap	Federal regulations unindexed in municipal pack

---

📝 Matter Workflow & Refusal-First Export

1. Two-Pass Grounding Gate (0.00% False Support Rate)

Every generated legal assertion undergoes rigorous two-pass validation:

1. Discrete Claim Decomposition: Extracts atomic legal propositions with their asserted citations.
2. Span Matching & Entailment Scoring: Computes lexical overlap and embedding similarity against retrieved authority chunks.
3. Hard Generation Constraint: If a model introduces an unretrieved statutory section, enforce_generation_citation_constraints automatically strips and annotates it: [UNAUTHORIZED CITATION STRIPPED: Section X].
4. Explicit Refusal & Abstention: If overlap falls between 0.15 and 0.35, or if authorities are missing, the claim is classified as abstain or invented_citation rather than falsely marked as supported.

2. Local Human Attorney Claim Feedback Loop

Attorneys review generated claims via the web UI or REST API (POST /api/cases/{case_id}/claims/feedback):

• Individual propositions can be marked as accepted, rejected, or modified.
• Corrections and attorney notes are recorded locally in the ClaimFeedback table, building a private gold-standard training set for future model calibration.

3. Refusal-First Document Export (.docx & .md)

When exporting memoranda (/api/consult/export/docx), refused or ungrounded claims are never smoothed into deceptive narrative prose. Instead, they are rendered as prominent STATUTORY COVERAGE GAP callout tables with red/amber borders:

┌────────────────────────────────────────────────────────────────────────┐
│ ⚠️ STATUTORY COVERAGE GAP: PROPOSITION UNGROUNDED IN RETRIEVED LAWS    │
├────────────────────────────────────────────────────────────────────────┤
│ Asserted Claim: Tenant entitled to automatic $10,000 statutory fine.   │
│ Cited Section: Section 999.99                                          │
│ Reason: Cited section does not exist in retrieved authority set.       │
└────────────────────────────────────────────────────────────────────────┘

Supported claims include verbatim supporting authority spans, ensuring full traceability from draft to statute.

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🏗️ Architecture

                               ┌────────────────────────────────┐
                               │    KruschLaw Web Interface     │
                               │  (Streamlit / 127.0.0.1:8505)  │
                               │   *Offline System Font Stack*  │
                               └──────────────┬─────────────────┘
                                              │ REST (CORS Restricted)
                               ┌──────────────▼─────────────────┐
                               │      KruschLaw Backend         │
                               │   (FastAPI / 127.0.0.1:8085)   │
                               │   *Lifespan Schemas & Guard*   │
                               └───┬────────────────────────┬───┘
                                   │                        │
                    SQL / pgvector │                        │ Local HTTP
                                   │                        │
            ┌──────────────────────▼───────┐       ┌────────▼────────────────────┐
            │   PostgreSQL 16 + pgvector   │       │      Local Ollama Node      │
            │   (Laws & Case Fact Vectors) │       │  ├─ bge-large (Embeddings)  │
            │        127.0.0.1:5435        │       │  └─ qwen2.5:14b / 7b (LLM)  │
            └──────────────────────────────┘       └─────────────────────────────┘

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💻 Hardware Requirements & Model Matrix

Profile	Recommended Model	Minimum Hardware	Expected Speed	Suitable Use Case
CPU / Lightweight	qwen2.5:7b + bge-large	16GB System RAM (8 threads)	~10–18 tok/s	Air-gapped laptops, small office CPU nodes, rapid exploration
GPU / Standard	qwen2.5:14b + bge-large	12GB+ VRAM (RTX 3060/4070, Apple Silicon 16GB+)	~35–55 tok/s	High-precision legal synthesis, nuanced exception spotting
Workstation / Heavy	qwen2.5:32b + bge-large	24GB+ VRAM (RTX 3090/4090, Apple Silicon 36GB+)	~20–30 tok/s	Complex multi-code statutory conflicts & lengthy appellate synthesis

To switch models, configure OLLAMA_LLM_MODEL in your .env file:

OLLAMA_LLM_MODEL=qwen2.5:14b
OLLAMA_EMBED_MODEL=bge-large

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⚡ Quickstart

Prerequisites

• Docker & Docker Compose
• Local Ollama instance (or use the containerized profile below):

  ollama pull bge-large
  ollama pull qwen2.5:14b

1. Clone & Configure

git clone https://github.com/kruschdev/krusch-law.git
cd krusch-law

cp .env.example .env

2. Launch Stack

Standard Air-Gapped Mode (Connects to host Ollama):

docker compose up --build -d

All-in-One Standalone Demo Mode (Includes containerized Ollama):

docker compose --profile with-ollama up --build -d

Verify endpoints:

• Frontend UI: http://localhost:8505
• Backend API Docs: http://localhost:8085/docs
• Health & Diagnostics: http://localhost:8085/health

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🗄️ Database Migrations (Alembic)

KruschLaw tracks its versioned statutory graph and audit log tables using Alembic:

# Run latest migrations
alembic upgrade head

# Generate a new migration
alembic revision --autogenerate -m "describe_change"

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🔄 Persistent Ingestion Worker

For massive multi-gigabyte municipal corpora, KruschLaw decouples file parsing from vector generation using a crash-resilient queue worker (src/backend/worker.py):

• PostgreSQL SKIP LOCKED: Concurrent worker instances consume pending batches without deadlocks.
• Byte-Level Deduplication: Uploads are fingerprinted via raw SHA-256 before parser execution.
• Resumable Offsets: If a batch or node crashes mid-stream, workers resume from last_committed_offset.
• Telemetry & Progress: Exposes batch-by-batch row counts and embedding progress via /api/ingest/jobs/{job_id}.

Run the standalone worker directly or let Docker Compose manage it:

python -m src.backend.worker

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📥 Ingestion & Datasets

Option A: Versioned California Legal Graph Fixtures

Click "🚀 Seed Paraphrased Demo Fixtures" in the sidebar (or run via curl):

curl -X POST http://localhost:8085/api/ingest/mock

Seeds 11 hierarchical records spanning California Civil Code (§ 1950.5, § 1954), Oakland Municipal Code (§ 8.22.020, § 8.22.030, § 8.22.360), San Francisco Administrative Code (Chapter 41A), Los Angeles Municipal Code (§ 151.09), and negative distractors (repealed § 1947.10).

Option B: LOCUS-v1 Municipal Parquet

Ingest municipal laws from the LOCUS-v1 dataset:

curl -X POST http://localhost:8085/api/ingest/parquet/async \
  -H "Content-Type: application/json" \
  -d '{"file_path": "/app/data/ingest/ordinances.parquet", "limit": 1000}'

Important

LOCUS-v1 License Notice: LOCUS-v1 is licensed under CC-BY-NC-4.0 strictly for academic and research evaluation. Commercial firms must ensure dataset rights before production ingestion.

Option C: KruschNexus Sovereign Document Ingestion (PDF / DOCX / EML / MD / TXT)

Ingest client contracts, leases, and evidence with page-true and section-true citations:

curl -X POST http://localhost:8085/api/ingest/upload \
  -F "file=@/path/to/lease.pdf" \
  -F "matter_id=1" \
  -F "doc_type=matter_facts"

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🔌 Model Context Protocol (MCP) Integration

KruschLaw provides a native stdio JSON-RPC MCP server (src/mcp/server.py) exposing air-gapped legal intelligence tools with mandatory guardrails:

Tool	Parameters	Description
search_ordinances	query, state, city, topic, as_of_date, limit	Hybrid lexical (tsvector) + vector search with authority weighting and temporal gating
get_section	section, jurisdiction	Retrieve complete section body, parent/child relationships, and amendments
log_matter	title, facts, matter_number, client_name	Securely log and vectorize client matter narrative on-premise
list_matters	limit	Enumerate active client matters and matter numbers
draft_brief	case_id, facts, title, city, as_of_date, limit	Stage 4-part legal brief with assertion grounding; refuses if authorities absent
get_grounding_report	case_id	Retrieve stored assertion grounding audit for a specific matter
get_code_traceability	doctrine	Inspect curated statute-to-code traceability invariants and verified mappings
resolve_controlling_law	doctrine, city, county, as_of_date, matter_facts	Multi-hop precedence resolution traversing preemption, amendments, and exceptions
detect_statutory_conflicts	jurisdiction, laws, as_of_date	Detect substantive conflicts (preemption, temporal sunsets, statutory exemptions)
explain_why_not_controlling	candidate_section, doctrine, as_of_date, city, county	Diagnostic report explaining why a section is superseded, preempted, or inapplicable
get_defense_checklist	case_id, as_of_date	Generate structured defense checklist with statutory deadlines and evidentiary audits
assemble_statutory_letter	case_id, letter_type, recipient_name, recipient_address	Assemble formal statutory demand letter or notice objection with mandatory citations

Guardrails for Agents

1. Refusal on Missing Authorities: If the air-gapped corpus does not contain relevant governing authorities, draft_brief rejects the request with CANNOT_DRAFT_WITHOUT_AUTHORITIES rather than hallucinating plausible statutes.
2. Review Mandate: Every draft includes review_required: true and provisional_work_product: true.
3. Discrete Claims Audit: Returns full side-by-side propositions, source excerpts, entailment scores, and failure classifications.
4. Citation Constraint Enforcement: Unretrieved statutory citations are stripped from generated prose prior to delivery.

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⚖️ Ethics, Compliance & Law Office Trial Protocol

KruschLaw is engineered around the ethical constraints of legal practice (ABA Model Rules 1.1, 1.6, and 5.3):

🛡️ Why Postgres + Ollama Instead of SaaS Vector DBs?

• Zero Sub-Processors: Cloud vector databases and hosted embedding APIs require data processing addendums and introduce subpoena risk.
• Zero Data Retention: On-premise Ollama instances do not log client facts to external training pools.
• Cryptographic Matter Hard Purge: An attorney can permanently delete a client matter and all associated embeddings/documents via DELETE /api/cases/{case_id}/purge, leaving only an anonymized cryptographic audit log.

📋 Law Office Trial Protocol

Usage Category	Permitted / Safe Operations	Prohibited / High-Risk Operations
Intake & Issue Spotting	Preliminary fact cross-referencing against municipal rent programs	Relying on AI drafts as final legal advice without attorney review
Statutory Exploration	Finding related definitions, exception clauses, and parent sections	Auto-filing generated pleadings in court
Citation Auditing	Flagging potential hallucinations, wrong propositions, and stale laws	Relying on unverified citations without consulting primary reporters
Discovery Review	Parsing client leases and contracts locally using KruschNexus	Processing non-matter third-party confidential documents without consent

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🧪 Automated Testing & CI Gates

# Run full unit, integration, and eval test suite (122 tests)
pytest

# Run 1-command precedence benchmark (DAG walk vs Naive Cosine RAG)
python scripts/demo_statutory_walk_vs_cosine.py

# Run 5-verb Sovereign Gateway MCP test suite
pytest tests/test_gateway_mcp.py -v

# Run statutory relations & preemption review queue test suite
pytest tests/test_statute_relations.py -v

# Run labeled grounding golden eval gate (0.00% False Support Rate target)
pytest tests/eval/test_labeled_grounding_eval.py -v

# Run golden retrieval and assertion-level grounding CI gate
pytest tests/eval/test_golden_eval_gate.py -v

# Run ruff code quality and lint gate
ruff check .

CI is automated on every push and pull request via .github/workflows/ci.yml.

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📊 Empirical Multi-Gate Evaluation Scorecard

KruschLaw is continuously benchmarked across five independent gates and an assertion-level grounding calibration matrix. All CI gates evaluate against frozen data without mocking embeddings or masking priority inversions:

python scripts/eval_retrieval_and_grounding.py

[Gate 1] Fixture Corpus Gate (Bootstrap Baseline)

Evaluates 25 realistic municipal and statutory fact patterns from data/eval/golden_legal_eval.json against the seed California legal graph:

Metric	Target	Measured Score	Evaluation Description
Recall@1 (Top-1 Accuracy)	> 85.0%	96.0%	Relevant governing statute returned as top hit
Recall@5 (Top-5 Coverage)	> 95.0%	100.0%	Gold section contained in top 5 retrieved items
Mean Reciprocal Rank (MRR)	> 0.900	0.980	Harmonic mean of gold citation retrieval rank
Distractor / Stale Law Leaks	0	0	Repealed or inapplicable statutes leaking as controlling
Mean Retrieval Latency	< 250 ms	127.2 ms	Hybrid lexical + semantic ranking latency

[Gate 2] Unmocked Embedding Gate (Real BGE-Large 1024-d Vectors)

Evaluates pure dense vector similarity across frozen, unmocked bge-large 1024-dimensional embeddings checked into data/eval/embeddings/:

Metric	Target	Measured Score	Evaluation Description
Pure Vector Recall@1	> 80.0%	100.0%	Top-1 accuracy using unmocked dense vector cosine similarity
Pure Vector Recall@5	> 95.0%	100.0%	Top-5 coverage across legal fact patterns
Pure Vector MRR	> 0.850	1.000	Dense vector harmonic mean rank without lexical hints

[Gate 3] Held-Out Statutory Gate (External California Provisions)

Evaluates 12 external California statutory and municipal provisions (AB 1482 rent caps, retaliatory eviction § 1942.5, repair-and-deduct § 1942, lockout penalties § 789.3, SF § 37.9/37.10B, Berkeley § 13.76.080, LA § 49.99, San Jose § 17.23) in data/eval/heldout_statutes.json:

Metric	Target	Measured Score	Evaluation Description
Held-Out Recall@1	> 60.0%	66.7%	Top hit accuracy across unseen external statutes
Held-Out Recall@5	> 90.0%	100.0%	Top 5 coverage across unseen external statutes
Held-Out MRR	> 0.750	0.799	Mean reciprocal rank on held-out provisions
Priority Inversions	0	0	Repealed statutes outranking controlling authorities

[Gate 4] Conflict-Pair Evaluation Gate (Deterministic Invariants)

Evaluates substantive legal conflict resolution across 5 deterministic statutory pairs (preemption, temporal amendment, and statutory exceptions):

Conflict Pair	Verification Invariant	Status	Result
AB 12 vs Repealed Cap	Post-2024-07-01 deposits capped strictly at 1 month	Passed	✅ 100.0%
County Island vs OMC 8.22	Unincorporated Alameda parcels exempt from city rent caps	Passed	✅ 100.0%
AB 1482 Duplex Exception	Owner-occupied 2-unit dwellings exempt from statewide Just Cause	Passed	✅ 100.0%
Corpus Abstention / Refusal	Abstains and refuses on novel issues missing controlling authority	Passed	✅ 100.0%
Exhibit Air-Gap Isolation	Zero leakage of confidential matter exhibits into public statutory index	Passed	✅ 100.0%

[Gate 5] Labeled Grounding Benchmark (labeled_grounding_golden.json)

Evaluates discrete proposition verification against the adversarial golden benchmark dataset across 5 taxonomy classes:

Metric	Target	Measured Score	Evaluation Description
False Support Rate	0.00%	0.00%	Invented, stale, or wrong propositions mistakenly marked supported
Golden Benchmark Accuracy	100.0%	100.0%	Accurate classification across all 13 labeled propositions
Abstention Accuracy	100.0%	100.0%	Low-overlap (0.15–0.35) claims routed to attorney human review
Citation Constraint Pass Rate	100.0%	100.0%	Unretrieved bare citations automatically stripped or flagged
Grounding Precision	> 95.0%	100.0%	Strict assertion verification precision

Grounding Calibration & Confusion Matrix

Empirical accuracy across 32 discrete legal proposition assertions:

Proposition Class	Tested Cases	Correctly Classified	Calibration Accuracy
VERIFIED (Supported)	9	9	100.0%
INVENTED_CITATION	9	9	100.0%
DIVERGENT_PROPOSITION	10	10	100.0%
STALE_REPEALED_LAW	4	4	100.0%
Overall Calibration Accuracy	32	32	100.0%

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📜 License

KruschLaw is open-source software licensed under the MIT License. Third-party corpora (such as LOCUS-v1) remain governed by their respective licenses (e.g. CC-BY-NC-4.0).