Results
Case studies
Every engagement, told the way we run them: the situation, the work, the result, and where people stayed in the loop.
National mortgage brokerage
Replacing an enterprise CRM saved roughly $500K a year
A brokerage was paying Salesforce enterprise prices for a CRM that fought how its people worked, and real AI meant Agentforce licenses on top. We built an AI-native replacement they own outright.
Read the case studyLegal services firm
Evidence document coding, two to three times faster with the same team
The firm codes evidence documents sent in by law offices, previously by hand, one at a time. An AI layer now proposes the coding and trained staff confirm it.
Read the case studyAccounting department
An accounting operation rebuilt around what AI should and shouldn't do
A process with no AI layer and a lot of manual hours now runs AI-first where it should, and the team itself owns the line between automated and human work.
Read the case studyMortgage brokerage · Underwriting
Underwriting knowledge, out of people's heads and into the system
Which lender takes which deal, what a complete file looks like: expertise that lived in a few people's heads now runs in software, which presents its work to underwriters for confirmation.
Read the case studyCold plunge studio
Knowing which promotions work and which clients are about to leave
The studio had bookings, visits, and memberships on record but no idea which promotions brought people back or who was quietly dropping off. We measure it from the data they already had, so the owner sees what converts and gets a short list of who to reach out to before they leave.
Read the case studyLongshore workforce
A shift-tracking app that helps longshore workers get paid correctly
Dispatch-hall schedules and layered pay rules made errors easy to miss. Our app tracks shifts and checks each week's pay against them.
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