Context
A product organization ran parallel AI pilots without shared standards for quality, cost, or release governance.
Business problem
Teams chose models ad hoc, skipped evals, and could not compare initiatives on business impact or operational risk.
User or operational pain
Leadership lacked a portfolio view; engineers and PMs duplicated learnings; customer-facing features shipped with inconsistent safety posture.
Product intervention
An operating model with intake criteria, model selection memo templates, eval rubrics, tiering strategy, and executive review cadence.
AI capability used
Cross-cutting patterns for RAG, agents, and copilots with shared observability and cost attribution by feature.
Samadhan's role
Samadhan advised on operating model, templates, and leadership rituals—grounded in production experience from HealthTech AI portfolios.
Business outcome
Faster decisions, fewer repeated failures, and clearer accountability from experiment to production.
Lessons for other companies
AI scale is an operating model problem. Templates and governance beat heroics.
Related service: Product Leadership Advisory · Insights
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