Overview
The AI Triage & Decision Automation Pilot helps organizations that manage high-volume, document-heavy claims use AI to streamline case handling without compromising quality. SteerBridge configures a secure, cloud-based workflow in your AWS environment that uses NLP, OCR, and machine-learning models to evaluate existing case evidence and propose structured outputs for reviewer approval.
The engagement begins by working with policy and operations stakeholders to define business rules, quality standards, and escalation paths. These inputs guide how cases are classified, which evidence is considered sufficient, and when human reviewers must intervene. SteerBridge then integrates with evidence repositories or content sources, implements OCR and NLP pipelines, and configures AI components to retrieve and summarize relevant information. Throughout the pilot, all AI outputs are subject to human-in-the-loop review, with clear audit trails and QA/QC sampling.
The work is structured around milestones such as system readiness, first successful AI-assisted form, and limited production for a defined claim type with agreed-upon accuracy and timeliness targets. Performance is measured through metrics such as reduction in manual review time, triage correctness, and QA pass rates, and the engagement concludes with an evaluation and roadmap for expansion. The resulting pattern can be replicated for additional claim types or programs using the same technical and governance foundation.
Highlights
- Reduce manual effort and unnecessary touchpoints by using AI to surface existing evidence and generate reviewer-ready documentation.
- Maintain high quality through human-in-the-loop review, structured QA/QC, and clearly defined performance metrics.
- Establish a repeatable pattern for AI-enabled decision support that can be extended to additional claim types, programs, or agencies on AWS.
Details
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