Good fit when you need
- An AI feature that must survive security and risk review
- Logs that explain what the model and tools did
- Evaluation before each prompt or model change
Service
AI Governance
Guardrails, evaluation, and audit trails so AI features stay inspectable in enterprise environments.
Overview
Controls you can show a reviewer
We help teams put policy into the product: who may use which model, what data may enter a prompt, which tools an agent may call, and how outputs are logged. This is engineering work—prompts, gateways, evals, and runbooks—not a certificate on the wall.
Where regulations or internal standards apply (including conversations about EU AI Act-style risk classes), we map practices to your legal counsel’s guidance. We do not claim ISO, CMMI, or AI Act certification unless you already hold it.
Capabilities
What we implement
The same pillars as the Zettai Framework, applied to AI delivery.
Scope lock
Use cases, data classes, and allowed actions are written down before prompts hit production.
Guardrails
Prompt filters, tool allow-lists, PII handling, and human approval on high-impact actions.
Quality SOPs
Change control for prompts and models, aligned with CMMI L2-style planned work and reviews.
Evaluation
Offline test sets for groundedness, safety, and regression after every material change.
Telemetry
Traces for prompts, retrieval hits, tool calls, and operator overrides.
Operating model
RACI for product, security, and engineering so incidents have an owner.
Benefits
Why teams choose this path
Make AI shippable in organizations that already have controls.
- Reviewers can inspect behavior instead of trusting a demo
- Prompt and model changes follow the same discipline as code
- Clear language with legal: practices and alignment, not invented certifications
- Works with Agentic AI and Enterprise RAG as the control plane
Process
How We Deliver
01
Risk map
Classify use cases and data sensitivity.
02
Controls
Define gates, logs, and allow-lists.
03
Instrument
Wire telemetry into the product path.
04
Evaluate
Stand up regression suites and review cadence.
05
Hand over
Runbooks for incident and change control.
Technologies
Tools We Work With
Control plane
PythonLangChainREST APIs
Observability
Audit logsEvaluationCI/CD
Cloud
Azure OpenAIAWSAzure
FAQ
Common Questions
We describe delivery practices aligned with CMMI Level 2-style SOPs (planned work, tracked issues, reviews). We do not claim a CMMI or ISO certificate unless separately stated with evidence.
No. We implement technical controls and operating practices. Regulatory interpretation stays with your counsel.
Often yes. We start with a gateway, logging, and evals around the feature you already have, then deepen controls as use cases expand.
Need AI that can survive a risk review?
We’ll map use cases, gates, and telemetry before the next production prompt change.