For CISOs & Security Leaders
AI is writing code faster than you can review it
Agent-generated code, prompts carrying sensitive data, and new injection surfaces are entering your repos daily. We help you put policy, scanning, and guardrails around all of it — without slowing the team down.
Compliance plus AI gets budget in any environment. We build the controls that let your engineers move fast with agents while keeping security and data governance provably intact.
What’s on your desk
Unreviewed AI-generated code in production
Volume is up and review capacity isn’t. Hallucinated APIs, missing tests, and subtle vulnerabilities slip through. You need automated, AI-aware scanning in CI.
Sensitive data leaking into prompts
Engineers paste secrets, PII, and proprietary data into prompts and tools. Without controls, your data is leaving the building one request at a time.
New prompt-injection attack surface
Agents that read external content and call tools introduce injection vectors traditional AppSec doesn’t cover. We map and mitigate them.
Data residency closes the easy path
For regulated workloads, hosted APIs aren’t an option. We stand up self-hosted inference so nothing sensitive leaves your environment.
How we’d help
The engagements that fit a Security Leaders best — each ships working software and a measurable result.
Production AI Eval Infrastructure
→Most teams shipped AI features with zero evals. We build eval harnesses, regression suites, online quality monitoring, and A/B infra for prompts and models.
An eval platform wired into your CI/CD
MCP Server Builds for Internal Tooling
→We expose your internal systems — Datadog, Linear, databases, deploy tooling — to AI agents over MCP, so your devs can work against company infra safely.
Internal MCP servers with auth, access control, audit logs
Self-Hosted LLM Infrastructure
→For data-sensitive teams (healthcare, finance, defense, EU): local inference, RAG pipelines, and fine-tuning workflows on infrastructure you control.
A working private AI stack on your cloud or on-prem
Agentic Codebase Readiness Audit
→We map your codebase against what actually makes it AI-coding-ready — module boundaries, test coverage, type strictness, docs, CLAUDE.md / rules files, and MCP potential — and quantify how far off you are.
A scored report + prioritized remediation roadmap
The proof is open source
We deploy the same infrastructure we build in the open.
Put guardrails around AI in your codebase
We’ll scope an audit of how AI-generated code and prompts flow through your org, then implement policy and scanning where it counts.