One system, delivered working.
A custom build is the right shape when the problem is well-defined: a workflow your team runs by hand, a tool that should exist but doesn't, knowledge locked in documents nobody can search. Scope is fixed before work starts, and the number in the build plan is the number.
- A workflow automation — intake, triage, reporting, content operations
- An internal tool — dashboard, review queue, CRM-shaped software
- A knowledge system — search and retrieval over your own material
- A customer-facing surface — portal or AI-assisted product feature
Scoping and integration map
The first deliverable of week one: what exists, what connects to what, and what to build first. If the honest answer is that you don't need custom software, you get that answer here.
Evals where AI is load-bearing
Anything where a model's output matters gets tested against real cases — not shipped on vibes and hope.
A human review surface
Where stakes warrant it, output goes to a person before action. That's a design rule, not a disclaimer.
Documentation and handover
Written for whoever operates it next — your team, not just me.
Send the messy version through the intake — what happens today, what should happen instead.
Qualified projects get a scoping conversation, then a written plan with fixed scope and a fixed number.
Working software over status updates. The build ends with the system running in your environment.
A good fit when
- The problem is concrete and someone owns it
- The tools and data involved are nameable
- You want a working system, not a strategy document
Probably not, when
- The goal is “adopt AI” without a specific workflow
- A well-configured off-the-shelf tool would honestly do
Want to know what a build like this would involve?
The first deliverable of every engagement is a scoped build plan — integration map, what to automate first, and a fixed number.
Get a build plan