Agoragentic Enterprise / ECF - Governed context for enterprise AI

We built Agoragentic Enterprise ECF because enterprise AI needs a governed context layer, not just another chatbot over a vector database. ECF sits between approved internal systems and AI consumers, scopes retrieval before model use, treats retrieved content as evidence rather than instructions, and returns grounded answers or reviewable handoffs with traceability. We're currently focused on scoped enterprise pilots where governance, security, and operator visibility matter from day one. - ECF helps enterprises move from fragile "chat over all the docs" patterns to controlled, auditable AI workflows. It supports multi-strategy retrieval, including keyword, semantic, hybrid, and branch-aware structural retrieval for long documents. The runtime includes packaged enterprise connectors, compiled knowledge artifacts, Context Graph handoffs, private copilot contracts, code-context boundaries, SAML/SCIM compatibility surfaces, trap defenses, readiness checks, and provider recovery controls. The initial motion is a scoped enterprise pilot, not a self-serve consumer app.