Dual-Model AI Submission Processing for a Multi-Carrier MGU
An end-to-end pipeline that reads 7–15 documents per broker submission, validates with Claude Opus and GPT cross-validation, and auto-populates Salesforce records.
The same data entered 3–5 times across disconnected systems.
An MGU within the Alliant Insurance ecosystem was running ~1,700 submissions per year across workers' comp, general liability, commercial auto, and excess liability. The same data was being entered 3 to 5 times — across Salesforce, Majesco/Coverall, Chubb's systems, Excel pricing models, and Epic billing.
With two new carrier markets coming online (AXA XL and Everest) alongside the existing Chubb relationship, the operation needed to scale to roughly 2,500 submissions per year without adding headcount. Approximately 70% of submissions were getting declined at various stages, and the principal had no real-time visibility into the book.
Salesforce → AI extraction → cross-validation → Cosmos DB → Salesforce.
Delivered through R Squared AI, Preisser Solutions architected and led delivery of an AI-powered submission processing pipeline. Broker submissions arrive via email intake, get classified by document type, and feed into an AI extraction layer mapped to a JSON schema aligned to Salesforce objects.
Two AI models cross-validate every extraction. Claude Opus runs as the primary extractor; GPT runs as the cross-validation engine. Any field falling below a 0.90 confidence threshold triggers the second model. Cross-document validation catches inconsistencies. Results land in Cosmos DB, then PubSub-sync back to Salesforce, with a custom human-in-the-loop review surface for low-confidence items.
Architecture and surface area.
Salesforce → PubSub → Azure AI Foundry → Cosmos DB → Salesforce data flow
Claude Opus as primary extractor; GPT as cross-validation model
0.90 confidence threshold triggers secondary-model validation on weak fields
Cross-document validation flags inconsistencies between submission documents
Custom Salesforce objects model submissions, lines of business, and quotes
Human-in-the-loop review surface built directly into Salesforce for exceptions
Document types ingested
- ACORD 125, 126, 127, 137, 130, 131
- Vehicle schedules (Excel)
- Loss runs (PDF and Excel across 40–50 carrier formats)
- Financial documents and broker narratives
Custom Salesforce objects
- Submission — the master submission record per broker package
- Line of Business — line-level data per submission
- LOB Quote — line-of-business quote tracking
- Submission Quote — submission-level quote rollup
- Submission Communication — broker correspondence log
Lines of business in scope
- Workers' compensation
- General liability
- Commercial auto
- Umbrella and excess liability
Outcomes the engagement actually produced.
Zero renewal slipped through in the first six months of the pipeline operating in production.
Commission reconciliation moved from a multi-day process to under 30 minutes per month.
The principal gained real-time visibility into the book — replacing rear-view reporting with a live view of every submission, quote, and bind.
The operation scaled toward ~2,500 submissions per year — across three carrier markets — without adding administrative headcount.
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Need to scale document-heavy operations without adding headcount?
Preisser Solutions architects AI document pipelines that read, validate, and route at the speed required to scale. Scoping begins with a conversation about your volume and your systems.