AI Agents

Context

Built for insurance within the Claims Processing stack and used by Claims teams, this agent focuses on a simple but constant bottleneck: making sure all required documents and photos are present before an adjuster can meaningfully assess a claim. It sits early in the file handling journey, right after FNOL and initial intake, acting as a gatekeeper for “is this claim actually ready to be worked?”.

What it does

The agent reads the claim type, product, jurisdiction, and channel, then applies your document checklist for that scenario—policy schedule, proof of loss, invoices, police reports, medical reports, repair quotes, photos, and any mandatory forms. It checks what is already in the DMS or claim record, spots what is missing, inconsistent, or unreadable, and updates the claim with a clear status such as “complete”, “missing X and Y”, or “unusable photo evidence”. Where something is missing, it can generate a simple request for the customer or intermediary using your existing communication channels, so that the file moves towards completeness without handlers having to chase manually.

Core AI functions

The core capabilities are checklist and document QA: mapping each claim to the right document requirements, checking presence and basic quality (e.g., file type, legibility, duplicates), and translating that into a simple, structured completeness status. The focus is not on deep legal interpretation but on reliably answering “do we have everything we said we need for this type of claim?”.

Problem solved

In many claims operations, missing or incomplete evidence is discovered late and repeatedly—handlers open a file, realise a key document or photo is missing, send a request, wait, and then repeat the cycle if the response is still incomplete. That drives avoidable delays and back-and-forth, and makes time-to-decision heavily dependent on individual diligence. This agent standardises that first gate, so missing evidence is identified and requested systematically rather than in scattered one-off emails.

Business impact

The direct impact is shorter time-to-decision and a smoother claimant experience. Handlers pick up more “decision-ready” files, spend less time chasing documents, and can focus their effort on assessment and negotiation rather than checklist policing. For the insurer, this means faster cycle times, fewer idle days waiting on evidence, and a more predictable flow of claims through the pipeline.

Integration and adjacent use cases

Integration complexity is low: the agent needs access to the claim record, the document repository, and your document requirement rules by product and claim type, plus a way to log completeness status and trigger standard outbound requests.

Common combinations in this stack:

• FNOL Intake & Triaging Agent to capture First Notice of Loss and route the claim correctly from the start,

• Policy Terms & Coverage Validator (Claims) to check the claim against policy terms, coverages, and exclusions once the file is complete,

• Damage Evidence & Estimate Extractor to pull structured damage details and draft estimates from images and documents,

• Eligibility & Threshold Checker (Claims) to validate deductibles, sub-limits, and other thresholds before payment, and

• Fraud Risk Signal Agent (Claims) to flag suspicious patterns from FNOL through to settlement so that SIU can focus on the right cases.