Archetypecore provides AI infrastructure designed to meet regulatory audit requirements, offering traceable pipelines, cited answers, and reproducible decisions. Their platform ensures every model run can be fully documented, enabling organizations to reconstruct decisions, verify model versions, and demonstrate compliance during legal or internal reviews. By integrating provenance and accountability features, they help regulated enterprises deploy AI safely while maintaining audit readiness.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations are deploying AI models faster than they can implement governance, leaving them unable to answer critical questions about model decisions, versioning, and compliance when issues arise.
Solution
Archetypecore offers an AI infrastructure platform built for regulated environments that records full provenance of model versions, data inputs, and execution details. The system enables exact reconstruction of decisions, providing traceable pipelines and cited answers that satisfy compliance, legal, and internal audit requirements. Clients begin with a risk assessment to identify governance gaps, then progress to a pilot implementation once a clear use case and team readiness are established. By integrating audit-ready data and model management, the platform ensures AI outcomes remain reproducible and accountable throughout their lifecycle.
Target Audience
Primary customers are enterprises in regulated sectors such as finance, healthcare, and insurance that need to deploy AI while meeting strict audit and compliance standards.
Features
- Automatic capture of model version, data lineage, and execution metadata for every inference
- Built-in reproducibility tools that allow exact decision reconstruction on demand
- Governance dashboards that surface provenance and compliance status in real time
- Risk assessment service to map current AI architecture against regulatory requirements
- Pilot deployment framework that accelerates transition from assessment to audit-ready implementation