Embedded Data & AI Partner for mission-driven organizations
Founded by Jasmine Daly — Fractional AI Leader, R/Shiny Developer, Open Source Contributor
Daly Analytics is a human-centric, fractional tech strategy & implementation firm serving nonprofits, universities, and mission-driven organizations across New England. I provide embedded Data & AI leadership, working alongside leadership and staff to develop AI policy, build internal capability through training, and deliver custom data-driven AI tools and workflows your team trusts.
We bring over a decade of expertise in data science, analytics, and engineering — with a little joy baked in.
Our clients include: national research organizations, conservation groups, universities, economic development agencies, and community-focused nonprofits.
🧭 Fractional Leadership — Embedded AI enablement engagements that give your organization strategic AI leadership without the full-time hire. Policy development, governance, and the steady hand of a senior hands-on partner.
🗺️ Tech Strategy — Platform assessments, roadmaps, and vendor evaluations that help you cut through noise and invest in tools that actually fit your mission.
⚙️ Custom Implementation — Production-grade builds, not prototypes. R/Shiny applications, automated reporting pipelines, and AI tools designed to scale with your organization.
📊 Analytics & Insights — Interactive dashboards and predictive analytics that transform messy data into decisions your team can act on.
🎓 AI Training & Capacity Building — Hands-on workshops including our values-driven framework for nonprofit AI policy, prompt engineering, and modern analytics practices.
Maintainer of four Comprehensive R Archive Network (CRAN) packages with 100,000+ total downloads:
Shiny developer since 2014. Active contributor to the R community through R-Ladies, R Contributors, and R Consortium initiatives including the CRAN Cookbook project.
Whether you're thinking through an AI policy, ready to embed strategic leadership, or need a dashboard your team will actually use, I'd love to hear from you.