FNOL and claims intake
Receive first-notification packs, classify the pages and extract the fields the claim needs.
Fields extractedWith their sourcesIndustry 01 · Insurance & Claims
Turn incoming claims and underwriting documents into evidence-backed work queues. Aviox builds AI-assisted intake, extraction, triage and servicing workflows while keeping accountable decisions, exceptions and approvals visible.
- 4workflows
- Insurance workflows described here, from FNOL to servicing
- 1 case study
- Published implementation, shown with its caveats
- Recommendation, not authority
- Accountable decisions and approvals stay visible
What can be automated
What can AI automate in insurance claims?
It can classify submissions, extract configured policy and loss information, check completeness, retrieve relevant internal guidance and route cases to the appropriate queue.
Claims and underwriting teams receive documents in many formats and spend much of their time preparing material before anyone can make a decision. Aviox builds AI-assisted intake, extraction, triage and servicing workflows that turn incoming documents into evidence-backed work queues.
Accountable decisions, exceptions and approvals stay visible. For material customer outcomes the workflow shows what was extracted, what source or rule was used, what recommendation resulted, what exception occurred and who approved the final action.
What we measure
- Time to first reviewTime from submission to a human or triage decision, on a definition agreed before the build.
- Manual first-pass rateThe share of cases that still need a person to sort them, with reasons.
- Decision traceabilityWhat was extracted, which source or rule applied and who approved the final action.
How we automate it
Insurance workflows we can engineer.
Four workflows where documents, rules and routing decisions meet, plus the rule that recommendation and authority are kept separate.
Claims-triage support
Prepare a reviewed, evidence-backed first pass so handlers start from the right queue.
Right queue firstEvidence attachedUnderwriting submission intake
Structure incoming submissions and flag missing information for the underwriter.
Gaps flaggedBefore reviewPolicy-servicing automation
Classify service requests, retrieve history and coordinate approved updates.
Approved updatesWritten back safelyRecommendation and authority
Show what was extracted, what source or rule applied and who approved the final action on any material outcome.
Approver recordedOn every material outcome| Process | Before | After |
|---|---|---|
| FNOL and claims intake | Packs read page by page by hand | Structured intakePages classified and configured fields extracted |
| Claims-triage support | An unsorted queue opened in order | Reviewed first passCases routed to the appropriate queue with evidence |
| Underwriting submission intake | Submissions chased for missing details | Structured submissionsInformation structured and gaps flagged |
| Policy-servicing automation | Requests read and routed manually | Classified requestsHistory retrieved and approved updates coordinated |
| Recommendation and authority | Decisions with no visible path | Visible decision pathExtraction, source, recommendation, exception and approver recorded |
Products for Insurance
Workflow patterns we build.
Three patterns for insurers, each configured to your documents, rules and systems of record.
Workflow pattern
FNOL and claims intake
Intake · Extraction · ProvenanceReceive first-notification packs, classify the pages and extract the fields the claim needs. Configured to your data, rules and systems, with review steps agreed up front.
- Fields extracted with page-level provenance
- Completeness checked before a handler opens the file
- Low-confidence fields routed for review
Workflow pattern
Claims-triage support
Triage · Queues · EvidencePrepare a reviewed, evidence-backed first pass so handlers start from the right queue. Configured to your data, rules and systems, with review steps agreed up front.
- Cases routed with the evidence attached
- Handlers keep the decision
- A review queue designed as a product
Workflow pattern
Underwriting submission intake
Submissions · Gaps · StructureStructure incoming submissions and flag missing information for the underwriter. Configured to your data, rules and systems, with review steps agreed up front.
- Submissions structured for the underwriter
- Missing information flagged early
- Underwriting judgment stays with underwriters
Note These are starting patterns we configure to your data, rules and systems they are not off-the-shelf SaaS See the products Aviox runs itself
Request a quote
Want this workflow in your organisation?
Share the workflow and we will propose a first pilot.
Request a quote
Where insurance work starts.
These are the insurance workflows we are usually asked about, listed as a starting point rather than a promise of payback.
- 01FNOL and claims intake
- 02Claims-triage support
- 03Underwriting submission intake
- 04Policy-servicing automation
- 05Completeness checks on incoming documents
- 06Evidence records for material outcomes
Compliance
Controls the insurer can inspect
Aviox does not certify your organization or claim your accreditations. We engineer technical workflow controls from the first sprint so that your own compliance and risk review has something to examine. The insurer and its advisers determine compliance with applicable requirements.
- Access control
- Data redaction
- Retention limits
- Decision records
- Human approval
- Audit trail
Connected
Everything this page plugs into.
Every industry page links to one relevant service, one relevant technology page and genuine proof where it exists: the service that does the work, the stack it runs on and where to read further.
The services doing the work
Service
Generative AI engineering
Grounded GenAI, retrieval, agents and document intelligence with evaluation, governance and human review.
Explore ServiceDocument intelligence
OCR, document classification, structured extraction, validation and human review.
Explore ServicesAI, automation, data and software engineering
Services scoped around the system you need to run, not a list of technologies you need to buy.
ExploreThe stack it runs on
Technology
AI and machine-learning stack
Model choice, retrieval, evaluation and observability behind claims workflows.
Explore TechnologyData platform stack
Governed pipelines and quality controls for claims and policy data.
ExploreRead further
Case study
AI-assisted claims triage
The baseline, evaluation data, controls and lessons from one implementation, with its results shown with caveats.
Explore All sectorsThe other nine industries
The same engineering pattern, adapted to each sector's rules, evidence needs and human-approval points.
Back to industries Request a quoteMap a claims workflow
A sentence about the workflow that slows you down is enough to start. An engineer replies, not a sales sequence.
Request a quoteQuestions
Before you get started.
Asked most often by claims, underwriting and operations leaders.
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Aviox positions AI as triage and decision support with human review. Automated assistance prepares evidence and recommendations; the accountable decision and any customer contact stay with authorized people unless the insurer has explicitly approved otherwise.
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Yes. Document intelligence combines OCR with structured extraction and validation, and routes low-confidence fields to a reviewer. Quality still depends on scan quality, so representative samples are tested before commitments are made.
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By grounding output in approved sources, constraining it to defined fields and schemas, applying deterministic checks, evaluating on representative and adversarial cases and routing uncertainty to a person.
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Yes. The AI claims triage case study describes the baseline, evaluation data, controls and lessons from one implementation. Its results are shown with the caveat that they are one engagement and are being verified with the client.
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No. It can classify submissions, extract configured fields and route work, but accountable decisions and exceptions stay with adjusters and underwriters.
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Against a baseline and an evaluation set that includes difficult and adversarial cases. The claims triage case study describes how this was done on one project.
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Typical claims and underwriting documents such as forms, correspondence, photos and policy documents, with extraction limited to the fields you configure.
Start a conversation
Map a
claims workflow.
Tell us how claims arrive, who triages them and what the system of record is. We will propose a baseline and a first production slice.