Screenshot of the Insurance premium audit exposure workbench interactive demo
Screenshot of the interactive demo, on sample data

Insurance premium audit exposure workbench

Reduce manual classification preparation while retaining auditable judgments.

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For
Commercial insurance audit teams reconciling declared business exposures
Solves
Payroll and sales evidence arrive in incompatible formats that slow policy exposure audits.
Delivers
Auditor-reviewed exposure reconciliation and question list
Built in
about 5 weeks of creation time, MVP in 6 days
Investment
$21,000 for the MVP, $50,000 for the full product
Run it
Inside your business, or as part of your offer to clients
01

What it does

Reduce manual classification preparation while retaining auditable judgments.

  1. Map source lines to proposed exposure categories.
  2. Surface ambiguous or excluded records.
  3. Reconcile totals to supplied control accounts.
  4. Compare the reviewed result with the recorded baseline and value assumptions.
  5. Capture corrections and named-owner approval before consequential use.
  6. Export a versioned auditor-reviewed exposure reconciliation and question list with source references and unresolved questions.

What goes in, what comes out

What the customer puts in
  • Authorized payroll or sales summaries
  • Policy-specific classification rules
  • Auditor notes

AI drafts, people review. Evidence review and quality assurance workspace.

What the customer gets
  • Auditor-reviewed exposure reconciliation
  • Question list
02

How it works

The workflow

  1. In
    Start with

    Authorized payroll or sales summaries, policy-specific classification rules and auditor notes

  2. 1

    Confirm the buyer's problem and scope

  3. 2

    Collect authorized payroll or sales summaries

  4. 3

    Policy-specific classification rules and auditor notes

  5. 4

    Then follow this sequence: 1

  6. Out
    Finish with

    Auditor-reviewed exposure reconciliation and question list

AI does the heavy lifting, people stay in charge

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One policy form; auditors approve classifications and any premium consequence. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Submission and rules, Evidence-linked exceptions, Reviewer decisions and export. Open on a review queue ordered by reviewer-selected priorities. Show each finding beside the original evidence and applicable rule. Provide accept, dismiss and needs-information controls with reasons. A separate report view summarizes confirmed findings and unresolved items, not raw AI flags. Make the task-specific outcome auditor-reviewed exposure reconciliation and question list visible beside its evidence, review state and value baseline.

Accounts and administration

Versioned review criteria, evidence links, reviewer decisions, disagreement handling, correction assignments, recheck status and exportable review history. Add organization access boundaries, named reviewers, usage caps, data retention controls, export logs and explicit approval for external actions.

Integrations and data access

Broker-approved policy documents, case records and carrier requirements. Source repositories, task trackers and report exports. Keep findings as review proposals until authorized owners accept the resulting actions. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

03

How we build it

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

  1. 1

    Scoping call

    Day 1

    Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

  2. 2

    MVP

    6 days

    One buyer segment, one recurring use case; first modules: map source lines to proposed exposure categories; surface ambiguous or excluded records. Manual review in the loop. Built by our AI software factory.

  3. 3

    Paid pilot

    7 days

    Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

  4. 4

    Full product

    3 weeks

    Self-serve onboarding, billing, monitoring and the wider integration set.

  5. 5

    Run and improve

    Monthly

    We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

  1. Pick the riskiest assumption. Here: will commercial insurance audit teams reconciling declared business exposures use it to solve "payroll and sales evidence arrive in incompatible formats that slow policy exposure audits"?
  2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
  3. Run a paid pilot. Agree quality and outcome thresholds before the pilot using this measure: Auditor time per accepted reconciliation and material correction rate.
  4. Measure, then decide. Track auditor time per accepted reconciliation and material correction rate; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Pilot scope: One policy form; auditors approve classifications and any premium consequence. Implement one approved input format, a bounded representative case set and the first two task modules: map source lines to proposed exposure categories; surface ambiguous or excluded records. Support the third module with operator review: reconcile totals to supplied control accounts. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.

After the MVP. Once paid pilots prove usefulness, automate repeatable reviewed steps and add one verified source integration. Expand supported inputs and case volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around auditor-reviewed exposure reconciliation and question list. Retain the explicit scope boundary: One policy form; auditors approve classifications and any premium consequence.

What the build depends on. Evidence coordinates, versioned rules, reviewer decisions and a representative reference set. Measure misses as well as confirmed findings before scaling. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One policy form; auditors approve classifications and any premium consequence.

04

Investment

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

  1. Phase 1

    MVP

    One buyer segment, one recurring use case; first modules: map source lines to proposed exposure categories; surface ambiguous or excluded records. Manual review in the loop.

    $21,000 · about 6 days of creation time

  2. Phase 2

    Paid pilot

    Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

    $12,000 · about 7 days of creation time

  3. Phase 3

    Full product

    Self-serve onboarding, billing, monitoring and the wider integration set.

    $17,000 · about 3 weeks of creation time

Indicative total, MVP to full product$50,000about 5 weeks of creation time · start with the MVP from $21,000

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

StageHosting and infrastructureAI usageTotal per month
MVP and paid pilotabout 3 customers$50–$100$80–$160$130–$260
Full productabout 50 customers$190–$380$880–$1,750$1,070–$2,130
05

Run it or resell it

Internally

For your own team

Commercial insurance audit teams reconciling declared business exposures run it inside the business: authorized payroll or sales summaries, policy-specific classification rules and auditor notes in, auditor-reviewed exposure reconciliation and question list out, reviewed by your people.

For your clients

As part of your offer

Agencies, consultancies and software companies can offer it to their own clients under their brand. We build and maintain it; you sell and deliver it.

Your brand, or this one

Run it under your own brand, or start from this concept style.

  • primary#279183
  • accent#c95477
  • surface#e4f1ef
  • ink#22201e
Headings
Archivo
Text
Lora
Voice
Reassuring, clear, no small print
Selling it to your own clients: the go-to-market playbook

Pricing to test

Test USD 500-2,000 for a defined audit sample and report. Offer recurring review priced by reviewed items and specialist hours. Software-only access can follow a reliable reviewed service. All prices require validation. Package the initial sale as one bounded auditor-reviewed exposure reconciliation and question list. Recurring fees must specify volume, review depth and integration support. For exchanges, test a disclosed coordination or successful-service fee rather than holding customer funds. Reprice only after measuring real delivery labor; platform-build cost is separate from a commercial pilot fee.

Message to test

Reduce manual classification preparation while retaining auditable judgments. Demonstrate a concrete auditor-reviewed exposure reconciliation and question list using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Commercial insurance audit teams reconciling declared business exposures professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample auditor-reviewed exposure reconciliation and question list from a small authorized input set, with a transparent calculation of auditor time per accepted reconciliation and material correction rate and no promised savings.

The first 30 days

  1. Week 1: interview five commercial insurance audit teams reconciling declared business exposures and inspect a recent example of payroll and sales evidence arrive in incompatible formats that slow policy exposure audits.
  2. Week 2: prepare a consented or synthetic demonstration of the three task modules.
  3. Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
  4. Week 4: measure auditor time per accepted reconciliation and material correction rate, reviewer effort and repeat-purchase interest. This is a demand-validation plan, not a thirty-day full-product delivery promise.

Paid pilot

Agree quality and outcome thresholds before the pilot using this measure: Auditor time per accepted reconciliation and material correction rate. Continue only if the buyer accepts the actual output, the intended job outcome improves without unacceptable errors, and measured delivery cost fits willingness to pay. Revise or stop if access is unavailable, qualified review cannot be provided, or apparent savings disappear after corrections and support. Use held-out cases when comparing model quality; use a properly reviewed comparison design before making causal claims. Record missing cases and negative results alongside successful outputs.

Success metrics

Auditor time per accepted reconciliation and material correction rate; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs auditor-reviewed exposure reconciliation and question list. Retain permissioned settings and reviewed examples, report realized value honestly, and sell increased volume or adjacent approved workflows only after contribution margin and quality remain acceptable.

Why clients would pick it

A domain-specific review rubric and rights-cleared examples of confirmed defects, false alarms and reviewer reasoning. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for commercial insurance audit teams reconciling declared business exposures. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

Manual reviewers, checklists, generic scanning tools and specialist audit services. Compare this product with the buyer's present method on auditor time per accepted reconciliation and material correction rate. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Document or media processing, model evaluation, expert review, false-positive handling, rechecks and customer-specific rubric calibration. Additional initial validation requires representative authorized sample preparation, buyer interviews, qualified domain review and bounded validation of auditor-reviewed exposure reconciliation and question list. Track cost per accepted output, including correction work, unsuccessful cases and support.

06

Safeguards

Separate document preparation from coverage, underwriting and claims decisions. Authorized professionals review policy meaning and customer commitments. One policy form; auditors approve classifications and any premium consequence. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.

Get this solution built

Built for you by our AI software factory, MVP in about 6 days. Tell us about your business and how you want to run it: inside your company, or as part of what you offer your clients. We reply within one working day.

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