METHODOLOGY · FDE
Your first AI use case, live in weeks
We put engineers inside your operations instead of mailing a spec to an outsourcer. One team owns the model, the integration, and the on-call. That is how your first real use case reaches production in weeks, not a deck the board reads next quarter.
Six principles
01
We work on your floor
Our engineers sit in your ops meetings, open your real data, and use your internal tools. We do not interview requirements out of you. We see them on the ground, where they actually live.
02
Score the use case before we build
We score and rank every candidate on impact, on how hard it is to ship, and on what could go wrong. Then we build the one your people will keep using after it goes live.
03
Something working every week
No months-long black box. You see a running version every week. The moment something is off, you say so, and the bet you have made stays small.
04
Evaluation ships with the system
Going live is not the end of the job. Every system leaves us with eval benchmarks and monitoring already running, so you manage quality by the numbers instead of by hope.
05
Built to survive an audit
Answers cite their sources. Processes leave a record. Models carry a card. In a regulated plant, AI that an auditor cannot read is AI you cannot ship.
06
The capability stays with your team
Delivery is training. When the project ends your team can run it, change it, and scope the next use case without calling us back. You own what we built together.
From one meeting to a system in production
PHASE 0 · 1 meeting
Use-case workshop
In one meeting we audit your processes and data, score the candidates, and set what success looks like. You walk out knowing your first use case, what it is worth, and how many weeks to launch.
PHASE 1 · 2–6 weeks
We embed and build
Our engineers work inside your environment and hand you a running version every week. The data pipeline, the evals, and the interface grow together, in the open, where your stakeholders can watch.
PHASE 2 · from week 6
Live, then wider
We ramp it up with monitoring and governance already in place, then take the pattern that worked to the next process and the next team. Your proof of concept stops dying in the lab.
On the ground
We see the real requirement, the one the spec missed
Our engineers sit in your ops meetings, open your real data, and use your internal tools. What we find on the floor rarely matches what the spec said. That gap is the problem worth solving.
Book a workshop
Coding together
Your engineers build it with us
Delivery is training. Your engineers pair with our team through the build, so when the project ends the ability to run it and change it stays in the building instead of walking out the door with the consultants.
Explore services
Watching the numbers grow
A weekly brief your leadership can actually read
Throughput, catch rate, hours saved: the live numbers for every workflow on one board. Your board does not wait for the quarterly report to know whether the AI is paying off.
See the delivery workspace
AI workflows,
built into your operations
We deploy forward — FDE and FDM — to build the AI agents and workflows your team runs on. Live in weeks, not quarters.