One company at a time. Locally hosted. Citation-grounded. Built after we've spent the time to actually understand how your operation works — not pulled off a shelf.
A useful brain has to know your operation the way your most experienced employee knows it. That kind of knowledge can't be installed from a vendor. It has to be built.
The market is full of "AI for [your industry]" products. They're trained on the average of an industry and tuned for the median customer. They get rolled out, they make decent demos, and then six weeks later they're sitting in a Slack channel that nobody opens.
We do the opposite. We spend the first month listening — to your operators, your tickets, your edge cases, the war stories your supervisors tell new hires. Then we build a brain that knows your business specifically. Not your industry. Your business.
Every brain we build is custom. We never reuse a deployment. We never scale to ship. And we say no to most of the work that comes through the door.
Most "AI projects" fail in week three because nobody bothered to learn the actual job before writing the code. We don't write code in the first month. On purpose.
30 days of structured listening. We sit in on calls. We read the playbooks. We shadow your top operators. We pull up the past year of tickets and look for the patterns nobody documented.
From the discovery brief, we design two parallel implementations: one that touches no customer data and ships immediately, and one that touches everything and waits for compliance. Same intelligence, two perimeters.
The non-secure build goes into production. The secure build runs on synthetic data in parallel. Every answer comes with a citation. Nothing leaves your network. The system is yours, not a license you rent.
60-day soak in real workflows. We measure hours saved, queue impact, escalation reduction. The brain isn't done because we shipped — it's done because your team is faster and your numbers moved.
These aren't marketing copy. They're the conditions we'll put on paper before signing a statement of work.
Every model weight, every byte of data, every working part of the AI runs on hardware you own. The "cloud" in this system is your office.
Every answer comes with its receipts. If the brain can't point at a source, it won't pretend to know. No fabrications dressed up as policy.
Customer data lives behind compliance, on its own server, with its own credentials. The useful build ships first. The regulated build waits for written approval.
You own the code, the database, the deployment. We hand off documentation and an escalation path. No vendor lock-in. No surprise invoices.
A regulated records platform serving over a million customers needed a system that could answer agent questions about operations, vendor processes, and marketing — without putting a single byte of customer data in front of a cloud LLM.
The brain shipped in two builds. The open build went live in week four with the operations corpus — playbooks, vendor reference data, marketing intelligence, system runbooks. The locked build was fully constructed on synthetic data and parked behind compliance sign-off, ready to flip when leadership says go.
Same intelligence on both sides. Different perimeters. Zero shared infrastructure between them.
A flag is a footgun. A separate database, on a separate host, with a separate credential, means the answer to "could the agent-facing brain ever leak a customer name?" is no, by construction — not "no, if the flag is set right."
SOPs, training, vendor reference data, marketing intelligence, system runbooks. Customer information is removed at ingest — never lands here. Ships in week four.
Customer records, communications, case detail. Identical interface to Build A — agents call the same tools. Different perimeter, different audit trail, written sign-off required to unlock.
We say no a lot. Not because we're precious about it, but because we only do this work well when the engagement is right.
We read every inquiry that comes in. If your situation is a fit, we'll set up a discovery call. If it isn't, we'll tell you that — quickly, and with a recommendation for what we'd do instead.
Start a conversation