For one of the world’s largest healthcare payers, the search for information had become a source of operational friction. Contact center agents — tasked with resolving a high volume of member and provider queries — were increasingly burdened by a knowledge management system that lagged behind their needs. The problem wasn’t the volume of information, but the inability to retrieve it accurately, efficiently, or contextually.
Persistent was brought to patch this inefficiency and rewire how knowledge was discovered, delivered, and deployed across the enterprise. The transformation journey that followed became a compelling playbook for organizations looking to scale Generative AI (GenAI) in a way that genuinely improves frontline performance and experience.
Diagnosing the Disconnect: When Knowledge Becomes a Bottleneck
What was happening on the frontline? With millions of subscribers and multiple business lines spanning healthcare benefits and services, the client’s contact centers were under pressure to deliver precise, real-time information.
Why the legacy system fell short: The platform was a legacy keyword-based engine that failed to interpret intent or surface relevant content. Agents had to “guess” the right keyword, only to be met with irrelevant results. Performance slowed during peak hours, increasing handle times, burnout, and inconsistency.
Bringing Semantics to the Forefront: A Context-Aware GenAI Solution
Persistent’s first principle was clear: don’t ask users to adapt to the system — let the system adapt to them. The goal was to evolve from keyword dependency to contextual understanding using a robust semantic search engine powered by GenAI.
Key Solution Components:
- Natural Language Processing (NLP): Interprets agent queries by meaning, not syntax
- Relevance-Based Ranking: ML-tuned results prioritize the most useful content
- Unified Knowledge Index: Multi-format ingestion consolidates all sources
- Auto-Scaling Cloud Infrastructure: Delivers high performances at peak load
Importantly, the user interface was kept unchanged and familiar to avoid disrupting agent workflows. While the backend was completely overhauled, the frontline experience became faster, more intuitive, and less cognitively demanding
Transformation in Action: From Search to Discovery
In side-by-side demos, agents ran identical queries in both systems. Legacy search returned scattered results; GenAI produced timely, relevant answers.
The outcomes were measurable and immediate:
- 150% improvement in search speed
- 40% increase in result relevance accuracy
- Reduced escalations and repeat calls
- Higher agent satisfaction and lower burnout
- Accelerated adoption across adjacent business functions
Persistent’s approach ensured the transformation wasn’t confined to a single team or use case. It triggered an enterprise-wide reassessment of how knowledge could be structured, accessed, and scaled.
Scaling with Intention: From Fix to Framework
Success at the pilot stage quickly turned into a broader initiative. The client expanded the initiative:
- Smart autocomplete for quicker queries
- Personalized content ranking via ML
- Cross-functional use across claims, compliance, provider portals
This wasn’t a one-off fix. Persistent’s platform became a “capability layer” —a flexible, scalable framework that other departments could plug into, reuse, and evolve.
Why Persistent: Strategic Execution with Human-Centered Design
What the client needed? A partner with domain expertise in regulated industries that could deliver trustworthy, scalable GenAI infrastructure.
What Persistent brought to the project:
- Proven healthcare and compliance expertise
- Cloud-native GenAI frameworks
- Human-centered design that respected user behavior
- Embedded collaboration with IT, business, and frontline staff
This was GenAI done thoughtfully applied as an infrastructure-level change agent.
Strategic Leap: From Pilot to Platform to Possibility
What started as a targeted initiative evolved into a structural shift. The organization moved from hunting for information to discovering insight; from reactive service to predictive support; from pilot enthusiasm to sustained execution.
The strategic transformation arc?
- From search to discovery
- From isolated fixes to systemic intelligence
- From reactivity to proactivity
Conclusion: From Replatforming to Re (AI)magining
Eventually, the transformation wasn’t defined by new interfaces or dramatic shifts. It was defined by thoughtful design, technical depth, and a singular goal: empower agents with the right information at the right time. By embedding GenAI into the core of search and keeping the frontline experience familiar, Persistent delivered a solution that not only improved response accuracy and reduced friction, but also restored trust in the tools agents rely on daily.
Want to explore how AI can become your enterprise’s most dependable teammate? Talk to Persistent’s AI Transformation Team.
