Agentic AI Flow for Claims and Compliance Decisioning
Boolean & Beyond built a multi-agent flow where specialized agents coordinate end-to-end claims processing with human oversight for risk-heavy decisions.
Overview
NexaSure processes large claims volumes across products with strict compliance checks. We implemented an agentic workflow that orchestrates document understanding, policy verification, fraud analysis, and recommendation generation in one controlled pipeline.
The Problem
Claims analysts were manually stitching together data from policy systems, uploaded evidence, and prior claim history. This slowed decisions, increased inconsistency, and overloaded review teams.
Key Challenges
Complex Multi-Step Decision Process
Claims required document extraction, eligibility checks, rule validation, and risk scoring. Existing workflows were linear, brittle, and hard to monitor.
High Manual Review Volume
Low-value, low-risk claims consumed analyst time because triage quality was weak. Teams had limited ability to prioritize high-risk cases effectively.
Fraud and Compliance Sensitivity
Automations had to respect policy rules, compliance constraints, and auditable decision traces. Every recommendation required explainability.
Lack of End-to-End Visibility
Operations leaders lacked visibility into where claims were stalling and which agents or rules were creating bottlenecks.
How We Built It
Process Decomposition
Mapped claims lifecycle into modular tasks and designed specialist agent roles for extraction, policy validation, fraud detection, and recommendation synthesis.
Agentic Orchestration Layer
Implemented supervisor-led routing with stateful checkpoints, retries, and human approval gates for high-risk claims. Added deterministic rule-engine integration.
Evaluation and Explainability
Built offline and online evaluation harnesses to test decision quality, false positives, and flow reliability. Generated structured explanations for each recommendation.
Productionization
Rolled out in controlled cohorts, tuned risk thresholds, and integrated outcome feedback loops to improve agent precision over time.
Solution Highlights
Specialist Multi-Agent Design
Dedicated agents handle extraction, verification, and scoring, while a supervisor agent coordinates sequence, confidence checks, and final routing.
Rule + LLM Hybrid Decisioning
Deterministic policy rules are combined with LLM reasoning to ensure both compliance reliability and contextual intelligence.
Human-in-the-Loop Risk Controls
High-risk or ambiguous claims are automatically escalated with evidence packets and rationale summaries for rapid analyst review.
Operational Flow Analytics
Dashboards show step-level latency, exception rates, and model confidence so teams can optimize throughput continuously.
Technical Deep Dive
The platform used a stateful agent graph where each node emitted typed outputs consumed by downstream nodes, preventing unstructured handoffs. Document extraction combined OCR pipelines with schema-constrained LLM parsing. A rules engine enforced policy clauses before any recommendation advanced. Fraud scoring blended gradient boosting models with agent-generated anomaly narratives for analyst readability. The supervisor agent maintained execution traces and confidence vectors, enabling automatic routing to manual review when thresholds were not met. This architecture delivered both speed and strict auditability.
AI Capabilities
Document Intelligence
Schema-level extraction from forms, reports, and supporting evidence
Policy Verification
Automated clause checks against product and eligibility rules
Fraud Risk Scoring
Pattern-based and model-based detection of suspicious claims behavior
Recommendation Generation
Explainable approve/review/reject suggestions with evidence references
Supervisor Orchestration
Managing agent sequencing, retries, and exception-handling pathways
Adaptive Thresholding
Dynamic routing to human review based on risk and confidence signals
Technology Stack
Agent Orchestration
AI/ML
Backend
Rules & Compliance
Analytics
Infrastructure
Results & Outcomes
-61%
Claim turnaround time
From submission to decision for low and medium-risk segments
-48%
Manual review load
Analysts focus on exception and high-risk claims only
+33%
Fraud catch rate
Higher detection before payout using hybrid scoring
+2.1x
Analyst throughput
Per-analyst processed claims increased with guided workflows
100%
Decision traceability
Every recommendation logged with evidence and rule lineage
-35%
Escalation delay
Faster routing of high-risk cases to the right reviewers
“Boolean & Beyond designed an agentic flow that our analysts trust. We gained speed, stronger compliance, and better fraud outcomes without losing control.”
VP Claims Transformation
NexaSure
Services Used for the Client Product
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