Use Case · AI Governance

Govern The Models, Prompts, And Tools Your Engineers Ship With.

Policy, attestation, and runtime controls over LLM usage across the SDLC. AI-BOM inventories every model and prompt your code touches, MCP-server allowlists scope what agents can call, and egress guardrails plus a full prompt audit log keep sensitive data inside your perimeter.

AI-BOM
Model + Prompt Inventory
MCP
Server Allowlist
100%
Prompt Audit Coverage
0
Sensitive-Data Leaks
What You Get

Treat AI Like A Supply Chain.

AI-BOM For Every Model, Prompt, And Tool

Inventory every model, system prompt, and tool definition your codebase calls. Track provenance, license, and version drift the same way you track packages.

MCP-Server Allowlist + Capability Scoping

Approve which MCP servers engineers can wire up, and scope their capabilities per project. Block unsanctioned servers at the IDE and CI layer.

Egress Guardrails + Full Prompt Audit Log

Sensitive-data egress guardrails strip secrets and customer PII before prompts leave your perimeter. Every prompt, tool call, and response is logged for audit.

Put Guardrails Around The Agentic SDLC.

Inventory the models, scope the tools, and audit every prompt before AppSec finds out the hard way.