Appeal Processing & Decisioning Agent
Accelerate resolutions with policy-aligned recommendations, without losing oversight.
Processing is where appeal costs and delays multiply - policy interpretation, documentation review, prioritization, and decision support are still heavily manual.
Quisitive deploys an agent-driven processing layer that integrates with Dynamics 365 and policy systems to standardize decisioning, reduce reviewer burden, and improve throughput.
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Appeal processing is where
delays become expensive
Appeal teams must triage cases, interpret coverage rules, review clinical documentation, and maintain auditability - often across fragmented systems. When policy application varies by reviewer, organizations get inconsistent outcomes and slower resolution times.
Why this is urgent:
What our Appeal Processing & Decisioning Agent Delivers
AI agents + policy intelligence + Dynamics 365
Solve what slows appeal processing today:
Manual prioritization and routing
Inconsistent policy interpretation
Time-intensive documentation review
Limited visibility into outcomes and trends
Over-reliance on expert reviewers for every case
Replace manual effort with orchestrated decision support:
Automated triage based on SLA, risk, and impact
Policy integration through connectors to retrieve coverage rules and prior decisions
AI recommendations with supporting rationale and confidence thresholds
Case enrichment and orchestration inside Dataverse/Dynamics 365
Human-in-the-loop validation that improves over time
Automatically triage appeals by urgency, financial impact, and risk - and route to the right reviewers.
Connect to policy systems using custom connectors; retrieve coverage rules and historical decisions.
Apply AI to produce recommendations with rationale, confidence thresholds, and escalation paths.
Coordinate processing steps across systems, teams, and downstream workflows while enriching cases in Dataverse.
Reviewers approve or adjust recommendations, creating a continuous learning loop for improved consistency.
FAQ
No. Reviewers validate recommendations and remain accountable for decisions; the agent layer reduces repetitive effort and improves consistency.
