TL;DR
Credence replaced hours of repetitive case review with an AI decisioning layer wired into their existing tools. The team kept their judgement; the platform took the volume.
The challenge
Credence handles a steady flood of client cases — most of them routine, some of them not. Senior people were spending hours a week on cases the system could have routed itself.
They wanted to scale without scaling headcount, and without losing the discretion their reputation depends on.
"FWS shipped in weeks what our last vendor couldn't in a year — and we actually understood every decision along the way."
What we did
- Decisioning model — built on historical cases with explicit confidence thresholds.
- Tight integration — wired into the platform the team already uses, no separate dashboard.
- Audit trail — every AI-influenced decision is logged with reasoning attached.
- Continuous evaluation — monitored weekly so model drift is caught early.
The model is the easy part. The real work is the integration — making it dependable enough that the team stops double-checking it.
The outcome
Manual review dropped by more than half, decisions-per-hour nearly tripled, and senior staff are free to focus on the cases that actually need their experience.
