We set up your company's entire AI operating system — not another tool, the system that ties all of them together. The best AI-native companies have made their whole organization queryable: every meeting recorded, every ticket tracked, every customer interaction captured, all legible to an intelligence layer that learns from it. We install that layer for you, end-to-end.
The result is a shift from an open loop to a closed one. In an open loop, you make a decision and check the results weeks later. In a closed loop, the system watches what's happening, compares it to what should be happening, and adjusts. That's the difference between a company that runs on AI and one that merely uses it.
Why This Is Hard to Do Alone
Most companies end up with a drawer of half-connected tools. Meeting recorders capture notes that go nowhere. Tickets, docs, and chat each live in their own silo. Enterprise search can tell you where something is but can't act on it. The market sells you slices; nobody assembles the whole loop.
- Capture tools (Granola, Fireflies, Otter) record but don't route work anywhere
- Work systems (Notion, Linear, Atlassian) hold artifacts but stay siloed
- Enterprise search (Glean) reads across tools but doesn't close loops
- Agent platforms (Dust) are powerful but left for you to configure and govern
- Forward-deployed consultancies build this — but only for the Fortune 500
What We Build
A strategist maps your operating model; a builder wires the plumbing. We don't hand you software — we deliver a working system and then hand you the keys.
- AI OS audit & blueprint — map your current tools, workflows, and where information leaks; design the target closed loop
- Meeting-to-action pipeline — every call recorded and auto-converted into tasks and tickets routed into Linear, GitHub, and your CRM
- Integration fabric — Slack, Linear, GitHub, Notion, CRM, and call recordings wired into one connected layer
- Queryable intelligence layer — ask the company anything across all artifacts and get sourced, actionable answers
- Self-improving memory — decisions, context, and outcomes captured so the system compounds instead of resetting
- Governance & guardrails — access control, data boundaries, and human-in-the-loop checkpoints
What You Get
A company that is legible to AI by default, queryable from day one, and improving on its own. We finish with playbooks, team training, and a tuning period so the OS runs without us.