Building data and AI systems you can prove.

Product and data leader focused on AI governance, synthetic data and enterprise data platforms in regulated industries.

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About

I lead product and data initiatives where correctness matters: healthcare, financial services and other regulated settings. My work centers on making AI and data systems trustworthy—enforcing deterministic guardrails around probabilistic models, ensuring auditable decisions, and generating test data that respects real-world constraints.

Product strategyData platformsAI governance & evalsSynthetic dataHealthcare & fintech compliance

Selected work

Data tooling

Aphelion

A constraint-safe, deterministic synthetic data generator for PostgreSQL and MySQL. Respects foreign keys, circular dependencies and exotic types, and has been validated on a 400-table e-commerce schema.

algomimic.com →
Causal data engine

Causal Foundry

High-performance Rust engine for causal synthetic data and real-time CDC shadowing. Enforces multi-table business invariants and streams privacy-safe synthetic events directly to Kafka and Parquet.

algomimic.com →
AI governance

Railproof

Deterministic rails for probabilistic AI agents in regulated workflows. Layered safety controls, replayable decision traces and audit-ready evidence for HIPAA and financial-services use cases.

railproof.com →

Writing

Publication

Architecture of Proof

Frameworks for AI accountability, governance operating models and verifiable decision-making.

architectureofproof.com →
Publication

World & Business

Analytical essays on AI, technology and how businesses actually change.

worldandbusiness.com →

Contact

Reach out for advisory, opportunities, or discussions on AI governance and data platforms. The best way to get in touch is directly on LinkedIn.

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