The AI colleague built into your GRC program.
Twelve specialist agents that draft policies, reconcile vendor signals, answer questionnaires with cited evidence, and route the right decision to the right human — all on your tenant-isolated data.
Mapped 12 of 14 controls to existing policies. 2 gaps identified — both in CC7 (System Operations).
Twelve specialists, one router
A team of agents — not one generic chatbot.
Every request is classified and routed to the right specialist. Vendor questions go to the TPRM squad. Policy and control work goes to GRC. Each agent is scoped to its domain and tools.
- 12 domain-specialist agents across GRC + TPRM
- 53 tools — every call audit-logged centrally
- Server-side org isolation enforced via contextvars
Grounded in your data
Every answer cites your real policies, controls, and evidence.
Tenant-scoped vector embeddings index your entire library. Effy retrieves the actual artifact, drafts the answer, and shows the receipts. Reviewers approve before anything ships.
- Tenant-isolated retrieval — never sees another customer's data
- Inline citations on every drafted response
- Adaptive confidence scoring — never phantom-penalizes empty data
Describe your access management process for production systems.
Production access requires SSO + hardware MFA. Quarterly reviews tracked in POL-AC-04. Just-in-time elevation for break-glass per CC6.3.
Auditor-grade by architecture
Defensible to your examiner — not just your auditor.
Every Effy tool call writes an AuditLog entry under EFFY_TOOL_<name>. AUDITOR role is read-only by architecture. PolicyVersion records are immutable once published. The integrity story is built into the data layer.
- 100% of tool calls audit-logged with org + actor
- AUDITOR mutation guard prevents any write across the agent surface
- Immutable PolicyVersion records on publish — never on draft
AI you can put in front of your auditor.
Effy was built for the regulated mid-market. Tenant isolation is architectural, not configurable. Every action is logged, attributable, and reversible by a human.
Tenant isolation
Vector embeddings, RAG retrieval, and tool calls are scoped to your org via server-side context — never the LLM input.
Full auditability
Every Effy tool call writes an AuditLog row. Reviewer overrides supersede AI scores. Nothing happens off the record.
AWS Bedrock
LLM access via STS AssumeRole — no shared keys, no prompt-data leakage to public model providers.
Questions, answered.
Latest on Effy AI.
See Effy AI at work.
30-minute walkthrough on your data model, with the specialist agents handling real questionnaire and vendor work end-to-end.