Show HN: ExtractQ cuts auto-insurance claim time 75% with zero-training AI

3 months ago 1

How ExtractQ turned a manual bottleneck into an AI-powered fast lane.

1. The Reality Check – Life Before ExtractQ

Every claim followed a five-hand relay:

  1. Intake – PDFs arrived by email; a coordinator downloaded, renamed, and filed them.
  2. Re-typing – A data-entry clerk keyed 30-40 fields into the claims system.
  3. Verification – Another employee cross-checked policy numbers and coverages in a separate portal.
  4. Chasing missing data – Gaps were kicked back to the clerk; adjusters waited.
  5. Audit & compliance – Screenshots and spreadsheets were stored for regulators.

Result? Slow resolutions, mounting backlogs, frustrated customers, and an audit trail nobody trusted.

2. The Game-Plan – What We Deployed

We introduced an AI-driven automation stack anchored by ExtractQ (for “zero-training” document intelligence) and a light-weight orchestration layer we call ProcessQ for validations and routing.

3. The New Groove – Life After ExtractQ

One straight-through, lights-out flow:

  1. Auto-capture – Claim docs drop into an S3 bucket or SharePoint folder; a serverless trigger picks them up.
  2. Smart extraction – ExtractQ reads the file, pulls exactly the fields we tell it to (no template training), and returns clean JSON.
  3. Instant validation – ProcessQ pings internal policy DBs plus third-party APIs (DMV, fraud-check, VIN lookup) to confirm accuracy.
  4. Seamless ingestion – Verified data lands in the core claims app via REST API; adjusters see a ready-to-adjudicate record.
  5. Built-in compliance – Every extraction, validation, and field-level change is time-stamped for auditors; dashboards refresh in real time.

4. Why It Worked

Traditional OCRExtractQ Advantage
Needs model training & upkeep“Just specify the fields” – zero training
Struggles with mixed layouts & handwritingVision-plus-LLM stack handles tables, photos, scribbles
Text onlyLinks data points for richer insights
Limited language support25+ languages out-of-the-box

5. Business Impact

  • Speed: Average processing time cut from 45 min to 19 min—customers get answers the same day.
  • Scale: When a hailstorm spiked claims by 150%, the system kept pace without extra hires.
  • Savings: Fewer manual touches translated to US $1.5 M annual OPEX reduction.
  • Decisions: Claims managers now approve or reject in one screen, backed by real-time accuracy scores.
  • Compliance Confidence: Auditors receive click-through evidence instead of CSV exports.

6. Takeaway

ExtractQ didn’t just digitize paperwork—it re-engineered the claims experience. By removing manual choke points and baking validation into the flow, the insurer turned a cost center into a customer-delight engine.

Ready to see your own “before and after” story?
Let’s run a pilot on five claim types and benchmark the results in under 30 days.

(Contact Scalong to schedule your discovery session.)

Read Entire Article