Results
What the work looks like.
Illustrative outcomes, and a note on what we build in each kind of engagement.
Six figures had been quoted for an “AI transformation”. The work that actually mattered was one process, running in five weeks. Invoices file themselves; the team checks the odd ones.
The first question we ask is where your data lives. Usually nobody else has asked it. The system runs on a box in your own rack, and your engineers get an answer with a source attached instead of a day of searching.
The only review that counts: is the team still using it in month three. That is the number we design for, not the launch.
Engagement notes
Before, after, and what we built.
Invoice intake, regional logistics firm
Before Three people, about two hours a day each, keying supplier invoices.
After Twenty minutes of review a day. Exceptions flagged automatically.
Built Document extraction, a MainStage AI workflow and an approval step. Runs in their environment.
Knowledge assistant, mid-sized manufacturer
Before Engineers searched five systems for specification history.
After One question, one answer, with the source document attached.
Built Retrieval over 40,000 documents, open-weight model on premises.
Client onboarding, accounting practice
Before Eleven emails per new client; nine days to the first deliverable.
After Two emails; three days.
Built An intake assistant and a document-checklist automation.
Note 3. The outcomes and engagement notes on this page are illustrative of the work we do, not case studies of named clients. No result is typical, and none is promised.
Tell us about the problem. We'll tell you honestly if AI is the answer.
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