We've mapped what works, what causes harm, and the structural conditions that distinguish the two — across AI readiness, scale strategy, and documented field deployments across India and beyond.
A four-dimension, four-stage maturity model for portfolio-level investment decisions — with stage-specific playbooks for what to fund and what not to fund, and self-assessments for both your portfolio organisations and your own internal team.
Read the framework → Field GuideMost foundations are funding AI enthusiasm. The ones doing it well are funding AI evidence. Five questions that tell you which is which — covering workflow clarity, data governance, evaluation design, government adoption, and failure modes.
Read the field guide → Field GuideScale is used to mean a dozen different things. This field guide maps three distinct types — Steady Impact, Linear Growth, and Exponential Impact — what each actually requires, and where AI has begun to change the geometry of what's possible.
Read the field guide → Case StudiesThree deployments that worked. Three that caused documented harm. The structural patterns that distinguish them — drawn from twenty government-supported AI deployments in India between 2023 and 2026.
Read the case studies → Field GuideWho owns the system controls the intervention. A four-question framework and four-tier ownership model for designing data architecture deliberately — before the first commit, not after the first failure.
Read the field guide →Working with funders and foundations on AI strategy. To discuss how these frameworks apply to your portfolio, write to shruti@tiltedground.com or book a call.
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