Five layers of control for every AI at your company.
Buddhi AI is the access control plane for AI agents. Every request passes through identity verification, policy checks, scoped retrieval, redaction, and audit logging, before a single token is returned.
Identity
Contractor via Claude Code
Policy Check
Scope “engineering”: DENIED
Scoped Memory
0 memories, access blocked
Redaction
Skipped, no content returned
Audit Log
Event recorded with timestamp, identity, scope, and result
Reason: Contractor role does not have access to engineering scope
Identity Layer
Every request is tied to a verified identity, not just a role, but a specific agent, acting on behalf of a specific person. Buddhi AI never makes decisions in a vacuum.
Policy Engine
RBAC policies define exactly which memory scopes each role can access. Policies are visual, editable, and auditable, with no hidden rules and no silent overrides.
Scoped Memory
Memories are tagged with scopes (engineering, finance, exec-comms, public-docs). When an agent queries Buddhi AI, only the memories matching their policy are returned.
API Authentication Flow
PR #142
Database Migration Strategy
Slack #eng
Component Naming Convention
Manual
Redaction
Even within allowed scopes, sensitive fields like PII, secrets, and credentials are automatically redacted before they reach the agent. Nothing leaks through.
Audit Trail
Every access attempt, allowed or denied, is logged with timestamp, role, agent, source, and result. Compliance teams get a complete, tamper-proof record.