Goldman Sachs
6y9m Chief Data Architect, building data systems inside a regulated enterprise.
Founder
Unmukt Raizada
Co-founder and CEO. 16 years at the intersection of data and AI, including 10 years building AI under audit standards at Goldman Sachs and JPMorgan, and co-founding Thena.
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Co-founder and CEO
Unmukt Raizada
16 years at the intersection of data and AI; 10 years building AI under audit standards across Goldman Sachs and JPMorgan; co-founder of Thena, backed by Lightspeed and First Round.
Unmukt leads company direction for TrustEvals: AI Strategy, AI Transformation, and AI Fluency with Governance, Audit, and Evals built into every build.
The discipline we sell is the discipline we hold ourselves to: every public number carries its real qualifier, whether stated, measured, modeled, or realized.
The public site shows one founder card for now; customers and partners remain anonymized unless explicitly approved.
AI systems in productionEvaluation and governance evidenceBoard-readable operating viewsArm's-length audit available
JPMorgan
VP Applied AI/ML, connecting model work to production decision environments.
Airtel / Wynk
AVP, data and product systems at consumer scale.
Thena.ai
Co-founder, backed by Lightspeed and First Round.
TrustEvals
Co-founder and CEO, leading the specialist AI builder for Strategy, Transformation, and Fluency with Governance, Audit, and Evals built in.
Data architecture
Goldman Sachs Chief Data Architect work across enterprise-grade data systems and operating constraints.
Applied AI / ML
JPMorgan applied AI and ML work where model behavior had to connect to real decisions.
Consumer-scale product
Airtel and Wynk experience building data-backed products at large user scale.
AI-native SaaS
Thena co-founder experience turning AI-heavy product work into enterprise workflows.
Evaluation systems
Production evals, harness engineering, and regression loops for systems that need to hold after launch.
Governance evidence
Framework-mapped evidence, owner cadence, and board-readable operating views for consequential AI.
Operating evidence for production AI.
Founder writing centers on evals, governance evidence, workflow measurement, and what leaders can actually defend once AI is in production.
Board, buyer, and practitioner rooms.
Talk tracks translate technical measurement into the executive questions: what is running, is it working, who owns it, and what proof exists today.
TrustEvals.
The measurement layer for trustable, reliable AI in production: Evals to prove behavior, Governance to preserve evidence, and services to make the platform land.