Agentic Intelligence Integration
Organizations adopting AI systems need governance frameworks that account for the people those systems affect. We deploy the EndogenAI methodology—an open-source approach to AI governance that your team can audit, own, and extend without vendor lock-in. This is the Red Hat model applied to AI accountability: free methodology, paid implementation. We help you embed governance into daily operations, not bolt it on after launch.
AI systems without accountability frameworks amplify existing inequities at scale. The EndogenAI methodology applies the Red Hat model to AI governance: free open-source framework, paid implementation support. Your team owns the methodology — we help you deploy it. Vendor lock-in is not part of the engagement.
What's Included
- EndogenAI Workflows methodology deployment (open source, auditable)
- Governance frameworks embedded into daily operations — not bolted on after launch
- Agent fleet design with value-encoding and posture constraints
- Bias and access impact assessments for agentic systems
- Audit-ready documentation your team can extend and maintain
Past Work
EndogenAI Workflows (dogma)
Open-source AI governance framework built for agent-driven development workflows — encoding organizational values into deterministic scripts, multi-agent orchestration patterns, and a structured scratchpad architecture. Now available as a cookiecutter template for adoption by other organizations.
Agentic Governance Advisory
Discovery and scoping engagements for organizations adopting LLM-based workflows — identifying accountability gaps, data lineage risks, and user-impact surfaces before deployment. Deliverable: a governance readiness report with prioritized remediation recommendations.
Access & Pricing
AI Integration engagements begin with a governance readiness assessment (typically 1–2 hours). Full engagements are scoped in 4–8 week phases. Schedule a discovery call to discuss your current AI stack, team structure, and accountability goals.