For Platform Engineering
Make agents first-class citizens on your platform
Your engineers want to use agents against company infra — Datadog, Linear, databases, deploy systems. We build the safe, audited paths that let them, plus the eval and observability layers underneath.
This is highly engineer-coded work, and very few people do it well. Our open-source ormai and openclawOS are the same kind of infrastructure we deploy for your platform.
What’s on your desk
No safe way to expose internal systems
Agents are boxed into the text of the repo because reaching the database or deploy pipeline isn’t audited or access-controlled. MCP servers fix that — done right.
No golden path for AI tooling
Every team wires up agents differently. You need shared slash commands, agent definitions, and templates that make the right thing the easy thing.
No observability for agents in production
When an agent misbehaves you can’t trace why. You need tracing, prompt versioning, and regression detection as platform primitives.
Readiness is a feeling, not a number
You can’t prioritize platform investment in agent-readiness without a score. We give you one, with a roadmap.
How we’d help
The engagements that fit a Head of Platform best — each ships working software and a measurable result.
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
Internal AI Coding Workflow Build-Out
→We standardize how your team uses Claude Code / Cursor / Copilot — custom slash commands, agent definitions, MCP servers for your internal tools, golden-path templates, and code-review hooks.
A working internal AI dev platform your team adopts
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
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.
Build the agent-ready platform layer
Tell us which internal systems your engineers most want agents to reach. We’ll scope the MCP and tooling work to get there safely.