A payments processor's reconciliation queue grew manually with transaction volume.
Reconciliation queues are now triaged automatically, with only genuine exceptions reaching an analyst.
- The problem
- A payments processor's reconciliation queue grew manually with transaction volume.
- What we built
- Confidence-scored classification against source-of-truth records before routing.
- The outcome
- Reconciliation queues are now triaged automatically, with only genuine exceptions reaching an analyst.
Case studies are anonymised at the client's request. Outcomes describe what changed operationally rather than claiming attributed financial figures — we'd rather under-state a result than dress one up.
The product behind this
Turn high-volume manual review into an automated, confidence-scored queue.
Automated document interpretation, evidence reading, classification and case routing for high-volume manual operations queues.
More Workflow Automation case studies
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A large share of manual workload was reclassified as automation-ready or assisted-review.
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A BPO servicing insurance claims had no systematic way to tell which claims needed a human decision.
The claims team now spends its time on genuine exceptions instead of routine evidence reading.
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Have the same problem?
Most engagements start as a single product on a single workflow, with a measurable result inside 8–12 weeks.