The Challenge: Claims Without Context
For even the most advanced payer platforms, one challenge remains unresolved: the vital context behind claims is trapped in unstructured content—clinical policies, provider manuals, appeals letters. While claim-processing is automated, context still demands manual interpretation. That’s where delays, disputes, and downstream costs begin.
One leading payer-platform provider recognized this wasn’t just a UX issue—it was a strategic product challenge. With expectations rising alongside Generative AI’s capabilities, they asked: Could claim adjudicators, policy specialists, and provider support teams access faster, more accurate insights from their sprawling content?
They didn’t need another chatbot—they needed a Generative AI fabric that could pull from every relevant source, explain its reasoning, and remain reliably compliant.
Automation without context is like diagnosis without history.
From Problem to Platform: A New AI Vision Takes Shape
Realizing the opportunity, the client turned to Persistent. What began as a search for insight quickly became a blueprint for transformation. The partnership didn’t aim to sprinkle AI over legacy interfaces—it reimagined the experience from the ground up, prioritizing precision, auditability, and user trust.
Building a Generative AI‑Powered Retrieval Engine
Together, the teams built a healthcare-tuned Retrieval Engine powered by RAG (Retrieval-Augmented Generation). This system delivered context-rich, source-cited answers to payer teams, eliminating ambiguity and accelerating clarity.
It pulled content from:
- Member handbooks & clinical policy documents
- Provider manuals, payment rules, appeals letters
- Historical case files & payer knowledge bases
LLMs parsed and ranked document segments, linking each answer back to its original source—fast, verifiable, and explainable.
Generative AI That Understands Payers
But healthcare workflows demand more than quick answers. Persistent built for real-world constraints:
- Show its work – Every answer came with citations to payer-approved content.
- Adapt to intent – Simple or complex, the system tuned tone and depth.
- Work within workflows – Deployed as widgets inside claims and support systems.
- Stay compliant – No training on PHI. No hallucinations. Just clear, compliant responses.
When answers are cited, contextual, and immediate – users don’t need training. They need trust.
Results That Compound Across Roles
The pilot targeted three high-impact roles: claims adjudicators, clinical policy reviewers, and provider reps. In each case, Generative AI turned friction into flow.
- 25–30% faster average claim resolution – Less time on documents, more on decisions.
- Fewer escalations – Source-aligned answers built consensus.
- Faster onboarding – New hires onboarded faster with AI-supported search.
And the industry trend backs this shift: According to BCG, nearly 40% of time in claims processing is spent on gathering and verifying information—not decision-making. This system flipped that ratio.
Meanwhile, the U.S. healthcare system spends over $60 billion annually—almost 25% of admin costs—on inefficiencies rooted in content ambiguity. Now, there’s a way forward.
Architecture That Adapts
Beyond the interface, the foundation made this sustainable.
- LangChain orchestration with multi-model fallback (OpenAI, Claude, etc.)
- Azure-hosted vector store indexing enterprise content
- Audit logs for every query, logging who queried, what was sourced, and which model responded.
This wasn’t a plug-and-play feature. It was a modular intelligence layer, future-proofed to evolve with AI model updates, policy shifts, and expanding content—without rewriting code.
Expansion by Design: From Use Case to Everywhere
Validated by real-world impact, the Retrieval Engine is now set to scale.
New roadmap milestones include:
- Case triage intelligence – Matching new claims to similar resolved ones
- Portal embedding – Generative AI-powered search inside member and provider portals
- Clinical reviewer assistants – Summarizing and contextualizing policy-backed opinions
From Differentiation to Monetization
The benefits went beyond internal gains:
- Differentiated UX – Cited AI answers removed friction and built trust
- Reusable prompt IP – Cross-department prompt chains simplified rollout
- New monetization models – Retrieval Engine APIs are now being explored as add-on products
This is Generative AI not as a feature—but as a growth enabler.
Why Persistent
Persistent brought the rare combination needed to deliver at healthcare-grade scale:
- GenAI prompt tuning and hallucination safeguards
- Embedded UX design for invisible AI adoption
- Enterprise rigor to handle compliance, fallback logic, and auditability
As trust is not a UI feature in regulated healthcare, it’s engineered into every interaction.
Every document now turns into an intelligent conversation.
Elevate your payer platform with secure, audit-ready Generative AI—built for clarity, compliance, and scale. Let your platform think, respond, and scale—with context-first intelligence.
