Eval first
Built the test harness on twelve years of anonymised case data, before any production code.
Shipped a RAG agent for case-officers, saved thousands of hours in the first quarter.
This is a representative engagement pattern, not a specific named client. Numbers are typical of the work we ship in this category. We share named references on a private intro call, with the client’s explicit permission.
6,000+
Hours saved · 90d
−70%
Avg case prep time
4.7 / 5
Officer NPS
A public-sector SaaS team wanted to ship an AI agent for case-officers, but couldn't afford the kind of incident a bad AI deployment would cause.
6,400 hours saved in the first 90 days, average case-prep time down 71%, and an officer NPS of 4.7 / 5. Zero policy incidents.
Brief us on your engagementBuilt the test harness on twelve years of anonymised case data, before any production code.
Retrieval pipeline, citation requirements, refusal logic, explicit policy gates.
Agent embedded in the existing case UI, pilot with a controlled cohort of case officers.
Phased rollout to all officers with weekly eval and feedback review.
By the numbers
Metrics agreed in week one, reviewed weekly with the sponsor and reported quarterly to the exec team.
6,400
Hours saved · 90 days
-71%
Avg case-prep time
4.7 / 5
Officer NPS
0
Policy incidents at rollout
"RAG-backed agent over years of case-law, trained against an evaluation harness and deployed inside the existing case-management product."
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