Two starting points, one practice. Pick the one that sounds like your week — the work runs the same loop: assess, automate, train, paid for by funding or written off as productivity spend.
“I need to bypass the productivity J-curve and access federal capital to automate my business.”
For SME operators chasing immediate ROI and cash-flow-positive automation. We map your build to the funding that pays for it — before a line of code is written.
Take the growth track Path B · Risk & Compliance“I need to deploy AI securely — AIDA-ready, data sovereign, without leaking corporate data.”
For C-suite, IT, and legal teams under scrutiny. Bounded, recoverable, human-in-the-loop systems engineered for AIDA readiness and Canadian data residency.
Take the compliance trackVendor-neutral by default. We use the tool that fits the job, not the one we resell — because we don’t resell any. Our full compliance posture lives on the risk & compliance track ↗
A triage agent pulls work off a queue, classifies it, scores its own confidence, and routes the edge cases to a human. Loops every minute or so. The code lives in your repo, not ours — your team can read it, change it, and run it without us.
An illustrative system, the same shape we ship. We hand over the repo, the eval set, the runbook, and the named owner on your side. How a project runs ↗
One on-ramp, then a tight loop — each engagement ships with a scope, price, calendar, and named outcome. No six-month discovery, no hand-off to juniors after the sales call.
We don’t publish client case studies — most work is internal or under NDA. Here is one illustrative pattern, the same shape we build. If it resembles a problem on your desk, that’s the conversation to start.
The workhorse pattern. Replace a multi-hour manual review with a 90-second extraction agent that scores its own confidence and routes the edge cases to a human. Evaluated against your real historical documents before it touches production.
Ranges are typical of real builds, measured against each client’s own historical data before launch. The screen above is an illustrative mockup, not a specific client.
The shape of a typical Chatbots & Agents engagement. Assessments and integrations follow the same rhythm at different lengths. We publish the calendar before kickoff, so there is no mystery about what happens when.
On site with the team. Watch the work happen. Decide what is worth building.
Write the evals before the agent. Ground truth from your real historical data.
First working pass. Crude but end-to-end. Shows where it fails, which is the useful part.
Tool calls, retries, cost ceilings, observability. Where most pilots quietly stop.
Live with two or three people. Watch what happens when a real human gets bored.
Runbook, evals you can rerun, named owner on your side, 30 days of support included.
We don’t sell capabilities. We sell better ways of working — then we hand them to the people doing the work, with the team that can run it without us.
Fixed scope and price, a named outcome, and a calendar agreed before kickoff.
Code in your repo, prompts in your docs, evals you can re-run. No proprietary glue.
Every build ends with a workshop where one of your people runs the system live.
Ten-week discovery phases that end in a PDF. Anything we’d need to subcontract to deliver well.
Every system sits inside the same four-layer posture. The full stack — mapped to the Voluntary Code and the federal Guide on Agentic AI — lives on the compliance track.
Canadian data residency. Onshore by design.
Level 1–2, read-only by default.
An approval gate before anything ships.
Immutable logs and a literal kill switch.
A thirty-minute call. We read your brief before we meet, then map the build to the funding that pays for it and the compliance posture it needs. If it is not the right fit, we will say so and point you toward someone better. If it is, you will have a scope and a price by the next morning.
We reply within one business day. No sales spam, and a 14-day out clause on every engagement.