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:
- Intake – PDFs arrived by email; a coordinator downloaded, renamed, and filed them.
- Re-typing – A data-entry clerk keyed 30-40 fields into the claims system.
- Verification – Another employee cross-checked policy numbers and coverages in a separate portal.
- Chasing missing data – Gaps were kicked back to the clerk; adjusters waited.
- 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:
- Auto-capture – Claim docs drop into an S3 bucket or SharePoint folder; a serverless trigger picks them up.
- Smart extraction – ExtractQ reads the file, pulls exactly the fields we tell it to (no template training), and returns clean JSON.
- Instant validation – ProcessQ pings internal policy DBs plus third-party APIs (DMV, fraud-check, VIN lookup) to confirm accuracy.
- Seamless ingestion – Verified data lands in the core claims app via REST API; adjusters see a ready-to-adjudicate record.
- Built-in compliance – Every extraction, validation, and field-level change is time-stamped for auditors; dashboards refresh in real time.
4. Why It Worked
| Needs model training & upkeep | “Just specify the fields” – zero training |
| Struggles with mixed layouts & handwriting | Vision-plus-LLM stack handles tables, photos, scribbles |
| Text only | Links data points for richer insights |
| Limited language support | 25+ 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.)
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