Forward-deployed.
Our engineers work from inside your operations rather than alongside them. That is not a service model — it is how the description gets written accurately, and how the software gets installed against it.
Understand
We spend the first week inside the operation rather than in a meeting about it — watching the work happen, reading the systems of record, and writing down the description that already exists in people’s heads.
- A first draft of your ontology: the objects, states and rules as they truly run
- The three workflows worth building first, with the reasoning for the order
- An explicit list of work that should be removed rather than automated
Engineer
The description gets wired to your real systems and real data, in your accounts, on your infrastructure. No sandbox, no synthetic dataset, nothing that has to be rebuilt later before anyone can use it.
- Integrations against your live systems of record
- Grounding, permissions and the test suite written before it meets a person
- Security and permission model reviewed with your team, not after
Deploy
It goes live with your team and your customers, at a size where a mistake is recoverable. We watch it under real load, correct what the description got wrong, and keep hardening it until it is boring.
- Staged rollout with a person in the loop where it matters
- Monitoring, alerting and a named owner on our side
- Runbook and handover written as we build, not reconstructed afterwards
Operate
We remain accountable for what we shipped. The description keeps changing because your institution keeps changing, and the next workflow starts once this one holds.
- Operational responsibility with a response commitment in writing
- Measured against the operational number agreed at the start
- The next workflow scoped only once the current one is stable
Software, and the description behind it.
Running systems
Deployed in your own accounts, against your own data, reachable by your own team without us in the room.
Your ontology
The description of your institution, as data, readable and editable by your own engineers.
The test suite
Real situations with the right outcome recorded, so the system can be changed safely after we are gone.
An exit that works
Data exportable on request, infrastructure in your name, continuity written into the agreement rather than left to trust.
Two stages, and you start small.
The first system is fixed in scope and fixed in price. It covers one workflow, and we put a real number against it on the first call — before you commit to anything, at no cost. You approve that number before work begins.
After it is live, most institutions move to a standing engagement. We operate what we built and engineer the next system. There is no long lock-in; institutions stay because the second and third systems are cheaper and faster than the first, the description already exists.
If we cannot see a path to production for what you are asking, we will say so on the first call and we will not quote for it.
Whether this is for you.
Usually a fit
- An institution where ten or more people lose real hours to repetitive work
- Systems that already hold your operational data
- Someone who can make a decision without a committee
- An appetite to change the operation, not only to observe it
Usually not
- A chat widget on a marketing site
- A proof of concept intended for an investor deck
- A procurement exercise looking for the lowest quote
- A mandate to adopt AI with no workflow attached to it
Tell us what your week looks like.
Thirty minutes. We will tell you what we would build first, roughly what it costs, and where this will not help.