INSURANCE WORKFLOW AUTOMATION

Custom AI applications built around how your insurance operations already work — not around a vendor template.

We help insurers, TPAs, MGAs, brokers, and claims teams reduce manual work across claims intake, policy servicing, customer support, reporting, and document-heavy workflows — without forcing your team into a new platform.

Book an insurance workflow review See insurance use cases
No platform lock-in. Human approval where needed. Built around your existing insurance systems.
Claims · call analytics · today live
1,284
Claims reviewed
0.72
Auto-routed cases
18
Needs human review
Adjuster · cases resolved · last 30d
M. Reyes78%auto · water
K. Singh52%auto · fender
T. Okafor38%property · roof
L. Müller84%auto · glass
S. Park22%liability
› show me calls where claimant mentioned water damage in last 30 days NLQ · pgvector
Outcomes we design for
Claims intake

Extract claim details, check missing information, and route cases faster.

Service conversations

Turn calls, emails, and notes into searchable customer records.

Carrier reporting

Prepare recurring reports from approved operational data.

Internal workflows

Connect documents, approvals, and systems without replacing your stack.

What we hear in discovery

Most operational drag isn't about one system. It's the gaps between them.

Insurance teams rarely lose time because one tool is broken. The delay usually comes from the handoffs between claims, policy records, emails, spreadsheets, document checks, customer calls, and approval steps.

01

FNOL details are rekeyed across systems

Claim details arrive through forms, emails, portals, or calls, but teams still copy the same information into claims systems, spreadsheets, and internal trackers.

02

Customer calls depend on scattered records

Agents often need to search across emails, policy documents, claim notes, and system screens before they can give a clear answer.

03

Policy and endorsement details stay buried in documents

Schedules, riders, exclusions, limits, and endorsements are often available as PDFs, but not as searchable operational data.

04

Manual reviews slow down routine claims

Simple claims still wait in the same queue as complex cases because routing rules, document checks, and exception handling are not automated.

05

Reporting takes too much spreadsheet work

Teams spend hours cleaning exports, combining data, and preparing recurring reports that could be generated from approved workflow data.

What we build

Custom AI applications for insurance workflows that are still manual.

We build focused AI applications around high-friction insurance workflows — claims intake, document review, policy servicing, customer support, reporting, and internal knowledge search.

Claims triage

Read incoming claims, route routine cases, and flag exceptions for review.

AI can extract key claim details, check required documents, identify missing information, and route routine cases while sending uncertain or high-risk cases to a human reviewer.

  • Extract claim details from forms, emails, and documents
  • Identify missing information before review
  • Route simple cases and flag exceptions
  • Keep human review for sensitive or uncertain cases
claims · last hour
Received
28
Auto-routed
21
Queued for review
6
CLM-44291Auto · rear-endAuto-acknowledged
CLM-44292Property · waterAdjuster queue
CLM-44293Auto · windshieldAuto-acknowledged
CLM-44294Liability · slipAdjuster queue
CLM-44295Auto · total lossInvestigations
Call analytics

Turn customer calls and notes into searchable service records.

Summarise calls, capture customer intent, connect the interaction to policy or claim records, and make past conversations easier for service teams to search.

  • Summarise service calls and customer notes
  • Connect conversations to claim or policy records
  • Help agents find previous interactions faster
  • Improve handoff between support and operations
call analytics · search
complaints about delayed payouts, last 7 days
#CALL-22841 · 4m 12s

Caller escalated about a water-damage claim filed 18 days ago. Asked for a supervisor twice.

#CALL-22906 · 7m 03s

Customer mentioned ombudsman; cited two missed callbacks on a property claim.

#CALL-22987 · 2m 41s

Auto claim — promised payout date missed. Caller asked for written confirmation of next steps.

Showing 3 of 14 matching calls · all linked to original recordings and adjuster notes
Policy & document extraction

Turn endorsements, schedules, and rider clauses into searchable fields.

Extract structured information from policy documents, endorsements, exclusions, riders, and schedules so teams can search and verify details faster.

  • Extract key fields from policy documents
  • Make clauses and endorsements searchable
  • Reduce manual document checking
  • Support faster internal review
policy extraction · audit view
POL-2024-08412 · endorsement #3
Commercial property — extended cover
versioned
Sum insured
AUD 4,250,000
Excess
AUD 5,000 / event
Flood
Included (sub-limit AUD 250k)
Business interruption
12 months indemnity
Reviewed by
Underwriter — confidence 0.92
Source
endorsement-3.pdf · p.2
Reporting & ad-hoc queries

Ask operational questions on top of approved insurance data.

Give managers a controlled way to ask questions about claims, service activity, policy data, and reporting metrics without giving unrestricted access to raw data.

  • Ask questions in plain language
  • Use approved reporting data only
  • Keep access rules and permissions in place
  • Support faster operational reporting
reporting · natural-language
loss ratio by product line, NSW, last 90 days
generated SQL · read-only view
SELECT product_line,
  SUM(losses)/SUM(premium) AS loss_ratio
FROM v_claims_90d
WHERE state = 'NSW'
GROUP BY product_line
Auto
64.0%
Home
58.0%
Commercial
71.0%
Liability
48.0%
Tell us where your insurance workflow slows down.
Tell us where your workflow is stuck — we'll review it and suggest the most useful next step, whether that's a prototype, a review, or a referral.
Request an insurance workflow review
How we work

From workflow review to a working insurance AI pilot in weeks.

We start with one operational workflow, define the data sources and approval rules, build a controlled pilot, and then prepare the path toward secure production use.

01
Week 1

Workflow review

We map the current workflow, systems, documents, approvals, pain points, and where manual work slows the team down.

02
Weeks 2–4

Controlled pilot scope

We define one practical use case, the required integrations, human review rules, and success criteria.

03
Weeks 5–12

Production build

We build the first working version with sample data, approved logic, and a clear workflow for review.

04
Ongoing

Security, approval, and rollout path

We plan access control, audit logs, fallback rules, production readiness, and the next rollout phase.

Compliance

Built with security and audit requirements designed in, not bolted on.

Insurance workflows involve sensitive customer, claim, policy, and operational data. That is why every pilot should be planned with access control, human approval, auditability, and secure integration from the beginning.

Controlled data access

Limit what the AI can access based on role, workflow, and approved data sources.

Human approval rules

Keep human review in place for sensitive decisions, uncertain outputs, and exception cases.

Audit trail and logging

Track what the AI read, generated, recommended, escalated, and who reviewed the output.

Secure integrations

Connect with existing systems through approved APIs, databases, documents, or workflow tools.

Discovery request

    Built for insurers, TPAs, MGAs, brokers, and insurance operations teams.

    Talk to us

    Claims move faster when internal workflows are easier to manage.

    Start with one workflow. We will review the systems, handoffs, documents, approvals, and reporting steps around it — then define a practical AI pilot.

    • Identify one high-friction workflow worth automating
    • Validate data, security, and integration constraints
    • Build a focused AI-assisted prototype
    • Plan production rollout with human review and audit trails
    Prefer email?
    info@voyantcs.com
    Common questions

    Insurance AI questions teams ask before briefing us

    If yours isn't here, send us an email — we'd rather have a real conversation than a marketing one.

    Engagement

    For tightly scoped pieces — a specific integration, a migration, a focused prototype — we can quote fixed price after discovery. For broader work, dedicated-team engagements work better because insurance requirements shift as the build progresses.

    You do. Every line we write becomes your property at delivery. We can host and operate it, hand it off to your team, or both — your call.

    A working prototype against your real data takes two to four weeks. A production system typically ships in eight to twelve weeks, with rollout planned in phases after that.

    Data & security

    We sign NDAs and DPAs before discovery. Encryption at rest and in transit is default; access is role-based and audit-logged. We can work inside your VPC or run dedicated infrastructure for your tenant.

    On AWS (EU regions for European clients) or on bare-metal Hetzner infrastructure in EU regions (Frankfurt by default). EU data stays in the EU when contracts require it.

    Four layers: input filtering, prompt constraints, output validation against structured schemas, and least-privilege access to downstream systems. Every model output is auditable; nothing reaches a payout, claims record, or policy without a validation step.

    Delivery & integration

    We've shipped REST, SOAP, file-drop, and direct database integrations across legacy and modern systems. For your claims and policy admin, we map to whichever interface is most stable: vendor API, scheduled file transfer, or read-only database replica.

    Whichever fits the problem. Whisper for voice; GPT-4o and Claude for structured reasoning; open-source models when fully self-hosted inference is required. We architect for swap-ability.

    Either side, or both. We can operate the application on infrastructure you own, hand the runbook to your platform team, or stay on as a support contract — whichever matches your operating model.