Three kinds of build, one standard across all of them.
Most projects start with one of the first three. All of them end with your team able to operate the system, read what it did, and judge whether it was right.
Client-facing systems
The public surface of your operation, built so an inquiry becomes a qualified, routed, recorded piece of work without anyone retyping it. Structured so search engines and AI crawlers read your expertise the way a person would.
What’s included
- Custom design and build, engineered around how work actually enters your business
- Intake that qualifies and routes as it collects, instead of dropping into an inbox
- Records written straight into the systems your team already works in
- Structured content and analytics, so you can see which work is worth more of your time
Workflow automation
The processes that run between your tools: intake, enrichment, document handling, reporting, follow-through. Built to run unattended, which means the edge cases and the failure paths get designed rather than discovered in production.
What’s included
- Your systems of record connected, so one fact lives in one place
- Multi-step processes that run to completion without a person shepherding them
- Explicit handling for the cases that break: bad data, missing fields, a service that goes down
- Documentation of what runs, when it runs, and what happens when it doesn't
Oversight systems
The line between what the system settles alone and what reaches a person. You set the thresholds, the system enforces them at the moment the decision happens, and everything it did stays inspectable afterward.
What’s included
- Thresholds you define, enforced in the flow rather than written into a policy
- Escalations that arrive with the context assembled, so the answer takes seconds
- Evaluation of what the model produces, so quality is measured instead of assumed
- A full record of what ran, what it decided, and what it decided on
AI literacy & training
Working sessions for the people who will operate and judge the system after handoff. The goal is a team that can tell a real capability from a demo, and that can move the thresholds themselves without calling anyone.
What’s included
- A working session on your own system and your own data, not a canned course
- How to read the logs and the evaluations, and what a bad result looks like
- A framework for assessing the AI tools and vendors that reach you later
- Enough understanding that the thresholds stay yours to move
Engagement, in plain terms
We start with a conversation
Not a proposal template. A working conversation about how your operation runs, where the exceptions live, and what a mistake costs, before anything gets scoped.
Pricing is scoped per project
Based on the system you actually need, not a package tier. You'll know the number before any work starts.
Ongoing support is optional
Most engagements are one-time builds, documented and handed over. Continued support is available, never required to keep the system running.