Evidence architecture
SQL-based evidence storage that captures every stage of the prediction pipeline, from raw data ingestion to final model outputs, with complete traceability.
AI Capital
Institutional AI Prediction & Risk Operating System
Microsoft for Startups | Azure A100 Infrastructure | Production-Grade AI
The Zevin Stocks Journal
Strategic market research and product intelligence
Chanan Zevin — CEO
Compliance layer
Complete audit trails and governance infrastructure for institutional AI systems.
A comprehensive governance framework that maintains complete evidence chains, audit logs, and compliance records for all AI operations, predictions, and decision processes.
SQL-based evidence storage that captures every stage of the prediction pipeline, from raw data ingestion to final model outputs, with complete traceability.
Built for institutional requirements with automated audit trails, version-controlled models, and reproducible research standards.
Dedicated governance dashboards provide visibility into system health, compliance status, and operational metrics for risk managers and auditors.
How to position it
This product page is written as an executive-facing briefing. It should explain what the product does, why it exists, and how it fits into the broader public platform before asking the visitor to click deeper.