This is Part 5. Start here if you’re new to the series.
In Part 4, we covered model flexibility, Task Personas, and practical RAG. But none of that matters if your security team won’t approve deployment. And they won’t approve what they can’t inspect.
The Black Box Problem
When companies fail with AI, it’s often not the technology—it’s the inability to answer basic questions. IBM’s 2025 Cost of Data Breach Report found 97% of AI-related breaches involved systems lacking proper access controls.
The Questions You’ll Face
From Security: What data accessed? What tools ran? Where did output go? From Legal: How did AI arrive at this decision? Where’s the audit trail? From Compliance: Which model version? What guardrails were active? From Audit: What happened step-by-step? Can I export this?
See Everything: Chiri Brain’s Answer
1. What Data Did It Retrieve?
Every RAG retrieval logged with document IDs, specific passages, relevance scores, timestamps, user context. Click through from answers to see exact source material. Export full retrieval chain for audit.
Example: Security asks “Did this AI access patient records inappropriately?” You show them query, retrieved collection (approved general protocols), did NOT retrieve patient records, audit trail immutable/timestamped/exportable.
2. What Tools Did It Run?
Every tool invocation logged: tool name/version, input parameters, output returned, success/failure, duration, user/context.
IBM 2025 data context: Unauthorized AI use compounds data risks. With Chiri Brain: see APIs called, review parameters, verify no unauthorized systems accessed, audit tool usage against policy.
3. Which Persona/Guardrails Applied?
Every interaction tagged with Task Persona name/version, system prompt in effect, allowed tools, output formats, active guardrails, Git-like diff if persona changed.
Example: Legal asks about instructions when generating customer communication. You show Task Persona version, key guardrails (PII redaction, citation required), full diff from previous version.
4. Which Model Was Called, and When?
Every model invocation logged: model name/provider/version, temperature/parameters, tokens used, response time, cost.
5. What Happened Step-by-Step?
Complete execution trace showing: request received, planning, retrieval, tool invocations, generation, validation, response delivered. Every step timestamped, logged, exportable, immutable.
What This Enables
For Security: Incident response with exact traces. Proactive monitoring with alerts. For Legal: Defensible decisions with full chain. Policy enforcement verification. For Audit: Efficient reviews querying full dataset. Continuous compliance monitoring. For Compliance: Regulatory confidence. EU AI Act transparency logs. HIPAA data access proofs.
The Bottom Line
When McKinsey’s 2025 survey shows only 6% are high performers and IBM finds 63% lack governance policies, it’s because existing tools make governance hard instead of natural. Chiri Brain treats transparency as the foundation.
In Part 6, we’ll cover how visibility becomes enterprise-grade controls for humans and agents.