Insurance subrogation AI that finds what your adjusters missed.

What most carriers get wrong on subrogation today

Adjusters are measured on cycle time, not on recovery. A file gets closed the moment the loss is paid — and the third-party liability signal on page seven of the police report quietly ages into the statute window. By the time anyone looks at it again, the recovery deadline has passed and the money is gone.

The industry response so far has been more workflow software: checklists, referral queues, adjuster reminders. None of that helps if the signal was never surfaced in the first place. The closed-file mountain keeps growing, and so does the pile of recoverable dollars buried inside it.

How ARBS Recovery Engine finds it

Upload a batch of closed claim documents. ARBS uses governed AI to read every page, every attachment, every note. For each candidate recovery, it pulls verbatim quotes from the source document with the exact location — “Loss description, paragraph 3”, “Police report attachment”. If the evidence isn't in the document, we don't make the claim.

Every surfaced opportunity arrives with a confidence score, the statute-of-limitations deadline inferred from the date of loss, a ranked list of missing evidence that would strengthen the demand, and a draft referral package your recovery team can send to the adverse carrier the same day. A human reviewer approves or rejects — the system never moves money on its own.

Every recommendation includes cited evidence, reviewer action, decision history, and an audit trail your compliance team can inspect. If a regulator or an adverse carrier asks how a recovery recommendation was reached, you can reproduce it line by line.

Closed-File Recovery Assessment in 14 days

Large platforms take a year to integrate with your claims system. We don't. Hand us a CSV of your last two years of closed claims; we'll hand back a ranked list of recoverable dollars with the referral packages attached — inside a 14-day Closed-File Recovery Assessment. If the numbers don't justify going further, you walk with the findings and no commitment.

What makes us different

• Evidence grounding with provenance. Every fact ties to a specific document location. Generic AI gives you plausible text; we give you citations.
• Governed audit trail. Cited evidence, reviewer action, and decision history are persisted on every recommendation. Compliance-grade reproducibility from day one.
• Per-client learning memory. The system learns your carrier's thresholds and your reviewers' rejection patterns. Generic AI resets every session; we get smarter with every decision your team makes.

We focus on a narrower, governed recoveries wedge that existing platforms don't solve well enough for our target buyer.