Building an enterprise AI architecture for healthcare and benefits
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Summary
April 8, 2025
In conversations with HR and benefits leaders across industries, we often hear a common question: "Oh, so it’s like ChatGPT?" It's a fair question. The explosion of simple AI applications has created the impression that enterprise AI might be equally straightforward to implement - just add an API call to an LLM and you're done.
Our experience at Avante tells a different story. The path to meaningful AI transformation requires far more than connecting to an API. It demands sophisticated data pipelines that connect siloed benefits administration systems, security frameworks that protect sensitive employee health information, and workflow orchestration that coordinates actions across HR teams, finance departments, and benefits consultants. A simple LLM interface can't reconcile inconsistent data formats between your third-party administrators (TPAs) and the proprietary analyses from your benefits broker. It can't maintain HIPAA compliance while sharing appropriate information with external partners. These challenges form the true foundation of enterprise AI - the hidden infrastructure that separates trivial demos from transformative business solutions.
The Real Challenges in Enterprise Benefits Management
1. Integration Across Organizational Boundaries Is Non-Negotiable
Large employers operate within a complex ecosystem of internal teams and external partners. HR teams work with their benefits consultants and brokers to navigate complex landscapes across benefits administration platforms, third-party administrators, wellness programs, and pharmacy benefit managers.
For AI to deliver real value in benefits management, it must seamlessly integrate not just internal systems but also the tools and workflows that connect employers with their consulting partners. This requires sophisticated connectors and data transformation pipelines that respect organizational boundaries while enabling fluid information flow across the entire benefits ecosystem.
2. Real Work Happens Across Teams and Partners, Not in Chat Windows
Perhaps the most important insight from our work in benefits: true value comes from addressing the fragmented nature of benefits management that spans internal teams and external partners.
Challenge: Establishing a Shared Language While Preserving Specialized Needs
Benefits ecosystems require a common vocabulary that bridges organizational boundaries. Each stakeholder - from HR teams to benefits consultants to finance departments - operates with their own terminology, priorities, and frameworks. Effective AI must translate between these specialized languages while preserving the nuanced requirements of each group.
For example, when discussing pharmacy benefits, HR may focus on employee satisfaction metrics, finance examines cost containment measures, and benefits consultants analyze clinical outcomes. Without a unified semantic layer that respects these different perspectives, communication breaks down into a game of telephone where critical details get lost in translation.
Challenge: Workflow Automation Beyond Simple Q&A
Consider the reality of how benefits work actually happens:
A benefits manager needs to determine if a specialty drug program is delivering ROI. Today, this process typically involves:
- The benefits team requesting program performance data from their broker or consultant
- The consultant manually collecting data from the pharmacy benefit manager portal
- The consultant creates a custom analysis in their proprietary format and sends it via email
- The benefits team then needs to reconcile this analysis with their internal finance data
- Multiple follow-up emails clarify methodologies and resolve data discrepancies
- After weeks of back-and-forth, they finally have enough aligned information to make a decision
This distributed process creates multiple points of friction, information loss, and delays. The benefits team, despite having knowledgeable consultants, still finds themselves caught in administrative coordination rather than strategic planning.
The real opportunity isn't in answering isolated questions faster - it's in creating a connected ecosystem where internal teams and external partners can collaborate seamlessly. AI's potential extends far beyond providing faster answers to include orchestrating complex workflows, maintaining context across interactions, and proactively identifying process bottlenecks.
Properly designed benefits AI doesn't replace consultants and brokers - it amplifies their expertise by eliminating the fragmented data collection and reconciliation that consumes everyone's time, while ensuring all stakeholders can communicate in their preferred terms and frameworks.
Building a Platform That Supports the Benefits Ecosystem
These challenges require a platform architecture that addresses the specific needs of the modern benefits environment. Rather than starting with AI capabilities and trying to retrofit them into existing operations, our platform begins with the reality of existing collaborative workflows, then enhances them with purpose-built AI components.
The Agentic Architecture: Specialized Intelligence Supporting Multiple Stakeholders
Our platform transforms benefits operations through specialized components. Some examples from our constellation of agents:
- Data integration agents connect and normalize information from TPAs, carriers, and point solutions
- Document processing agents extract relevant information from benefits guides, plan documents, and policy information
- Collaboration agents facilitate secure information sharing between employers and their brokers/consultants
- Employee engagement agents provide personalized guidance through email, Slack, Teams, and CRMs like ServiceNow, Zendesk, and Zoho Desk
- Analytics agents identify trends and insights in plan performance and utilization
- Orchestration agents coordinate the overall process flow and manage exceptions across organizations
Each agent focuses on what it does best, creating a system that respects the specialized roles of both internal teams and external partners while eliminating the friction that typically exists between them.
Bridging Structured and Unstructured Data Across Organizations
One of the most technically challenging aspects of benefits AI involves connecting unstructured human inquiries with highly structured benefits data - especially when that data spans multiple organizations with different terminologies and data models.
Employees ask questions in natural language ("What's my deductible for therapy?"), HR teams need specific plan details from their consultants, and finance teams require structured reports in their preferred format. Meanwhile, brokers and consultants have their own analytics platforms and reporting methodologies.
This multi-layered disconnect requires a semantic layer that maintains mappings between natural language concepts, technical implementations across benefits systems, and the proprietary frameworks used by consulting partners.
For example, when a benefits leader asks a seemingly straightforward question like "How many of our employees are getting preventative care?", our platform must navigate a complex web of terminology and data structures:
- In the employer's HRIS system, employees might be categorized by department codes, employment status flags, and benefit eligibility markers (e.g., "FT-EE-ELIG")
- In the medical claims database, preventative care could be represented by hundreds of different CPT codes (e.g., 99381-99387 for preventative exams, 77067 for mammograms, 45378 for colonoscopies)
- In the carrier's reporting portal, these might be grouped under a proprietary category called "Wellness Visits" or "Preventative Services"
- The benefits consultant's analytics platform might use another proprietary classification system that groups these services into "Primary Prevention" and "Secondary Prevention" categories
- The pharmacy benefit manager might track preventative medications using entirely different coding systems and categorizations (like GPI drug classes)
Without a sophisticated semantic layer, answering this simple question would require manual extraction and reconciliation of data from each system, followed by complex transformations to align the different coding systems. Our platform handles this complexity through a combination of domain-specific knowledge bases, relationship maps between terminology systems, and AI-powered classification that identifies equivalent concepts across different data models.
The result is that stakeholders can interact with the system using their natural terminology, while the platform handles the complex translation to and from the structured data formats used across the benefits ecosystem.
Beyond the Wrapper: How Our Platform Transforms Benefits Management
Benefits management represents a complex challenge precisely because it spans organizational boundaries and extends across the entire benefits lifecycle. Avante's platform addresses these challenges through:
- Secure connections to both internal systems and partner-managed platforms
- A unified data model that normalizes information while preserving its lineage
- Communication capabilities that integrate with collaboration tools used across organizations
- Customizable workflows that respect different roles while facilitating seamless handoffs
As we continue to develop our platform, several principles guide our approach:
1. Enhance Partnerships, Don't Disintermediate Them
Rather than attempting to replace brokers and consultants, our platform amplifies their value by eliminating administrative burden and providing richer analytical foundations. This allows trusted advisors to shift their focus from data gathering to strategic guidance.
2. Support the Entire Benefits Lifecycle
Benefits management isn't a collection of discrete tasks - it's a continuous cycle of planning, implementation, monitoring, and refinement. Our platform supports this entire lifecycle, providing continuity across annual renewal periods and creating institutional memory that persists even as team members change. This comprehensive approach ensures that insights from one phase inform decisions in the next, creating a virtuous cycle of continuous improvement.
3. Build for Multi-Stakeholder Alignment
Perhaps the greatest opportunity in benefits AI is creating alignment across previously disconnected stakeholders - HR, finance, employees, brokers, consultants, and vendors. Our platform is designed to facilitate this alignment by providing a common foundation of information while respecting the unique perspectives and needs of each participant.
Conclusion
The "GPT wrapper" myth misses what truly matters in enterprise AI. Building effective benefits AI requires more than connecting to an LLM - it demands robust infrastructure that connects disparate systems, bridges organizational boundaries, and orchestrates complex workflows across teams and partners.
This technical foundation enables something far more valuable than faster Q&A. It frees HR teams from administrative busywork, gives consultants better tools to deliver strategic guidance, and provides employees with personalized support when navigating their benefits.
Our vision isn’t just about building better benefits, it’s about building better workplaces. When employees can easily access the care they need and HR teams can focus on people rather than paperwork, organizations can create environments where people genuinely thrive. That's the true promise of enterprise benefits AI.
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Related content
Case Study
How Samsung’s benefits team became AI-native
Challenge
A benefits program running on disconnected data
Samsung Semiconductor’s benefits team was running a multi-million-dollar program, but their data couldn’t tell them whether it was working the way they intended, or help them shape strategy and make the case for change to leadership. Claims, Rx, dental, vision, point solution, and wellness data all arrived directly from vendors, each source on its own, never reconciled, leaving the team no way to reason across them.
The pressure came to a head at renewal. Samsung’s point solution contracts were all up at once, and the performance guarantees underneath them rested on each vendor’s own anticipated ROI, quantified largely from employee attestations rather than objective data. Sarah Schutzberger, Samsung Semiconductor’s Benefits and Wellness Sr. Manager, who is responsible for the entire program, wanted to stop relying on fragmented information and tie every point solution back to actual claims. At the same time, with the team scaling for growth and employees increasingly expecting AI-grade speed, she wanted to modernize the employee experience too.
“Everything before Ava was fragmented. We relied a lot on the data being provided directly to us from our vendors. Now we’re able to connect the dots between each of our benefits to truly understand the employee impact.”
Sarah Schutzberger
Benefits and HR Operations Sr Manager, Samsung
Solution
Two agents, one connected platform
Samsung Semiconductor deployed Avante’s AI-native benefits intelligence platform. It securely brings together claims and eligibility, point solution data, plan documents, and the vendor contracts behind them into the Vault, and two purpose-built AI agents sit on top of that shared foundation. For most benefits teams, those sources never connect. With Avante, they do.
Ava
Ava, the agent for the benefits team, reasons over all of it, reconciling vendor contracts and reports against the actual claims on demand. It can generate reports and build branded presentations. The team can bring its own data too, uploading spreadsheets, PDFs, and files into a conversation. It acts like an expert benefits teammate that knows the company, its programs, and its goals, and delivers objective, near real-time insights when they’re needed. “I was looking for a data warehouse,” said Sarah, “and this is so much better. Instead of static dashboards or sending requests to an analyst, I have real-time insights at my fingertips on any question I have.”
Screens are illustrative. Names and data shown are fictional to protect user privacy.
Carly
Carly, the agent for employees, gives Samsung’s workforce real-time, accurate answers to benefits questions, and prompts the right next step rather than answering only the literal question. It helps employees find and use benefits they did not even know they had, at the exact moments they need them most.
Screens are illustrative. Names and data shown are fictional to protect user privacy.
Together, the two agents give the entire company a complete picture of its own benefits, making the use cases below possible for the first time.
Results
What the team does with Ava
The use cases are virtually endless, from building reports to making the case for new programs, from developing customized communications to pressure-testing plan redesign decisions. These are just a few the team acted on in its first three months with Ava.
Use case 1: 66% increase in Lyra utilization
Lyra had traction, with strong engagement and a high share of employees in care relative to its book of business. But when the team dug into behavioral health using Ava, they were able to compare utilization across Lyra and the medical plan, the EAP and the carrier, two datasets that almost never get connected. They surfaced a gap they could not have seen before: a large share of dependents, especially children, were routing through the medical plan for behavioral health instead of starting with Lyra, where the team wants people to begin. The stakes are meaningful: care comes in on day one through Lyra, versus waits of two weeks or more through the medical plan.
The team used Ava to draft communications for that exact parent-and-dependent population, timed to Mental Health Awareness Month, and sent them that week. They also took the finding back to Lyra so it could sharpen its own outreach, and opened a conversation with the medical plan provider about surfacing Lyra first inside the portal. The result: from the first communications in May through the end of June, engagement with the dependent population improved and utilization increased 66%.
“It was a ten-minute chat with Ava that gave us key insights, so we could make targeted communications and address the exact gap instead of throwing spaghetti at the wall and sending out marketing materials that weren’t necessarily hitting.”
Cara Ayala, RD, CPT, CHC
Wellness and Benefits, Associate Manager, Samsung
Use case 2: Making the case for healthier food options
As dietitians, Sarah and Cara had wanted to address nutrition through the company café for years, and the project kept getting pushed aside. Working from the claims data, they pulled the disease states most influenced by nutrition, gave Ava their clinical guidance (whole-foods-first, plant-forward, lean proteins, healthy fats, and a simple green/yellow/red system employees could follow), and used Ava to produce an evidence-based meal program.
The café team now plans to use this framework during the current RFP process to ensure the new vendor is able to execute successfully. Additionally, the team will track the changes in their food program along with medical claims to see the impact. A project that had waited years came together in a single 2-hour planning session.
“Revamping our cafe and food options has been a passion project of ours, but it’s a project that gets pushed to the wayside year after year. But with Ava, it is now possible to move forward.”
Cara Ayala, RD, CPT, CHC
Wellness and Benefits, Associate Manager, Samsung
Use case 3: Building an airtight sabbatical program ROI proposal
Hortencia Alcazar, the Senior Benefits Analyst at Samsung Semiconductor, had built a sabbatical analysis by hand about two years ago. It took two to three weeks of research, formatting, and modeling. She rebuilt it this year with Ava, and it came together in a few hours. Ava pulled in turnover, mental health burnout claims, replacement cost, and tenure assumptions to model ROI at different vesting points, then packaged the work as an executive summary and slides ready for leadership. What stuck with Hortencia and the team was that when they tried to trick it with the data, it held its logic and double-checked them, reasoning exactly as they would have. The proposal is now slated for Samsung’s 2027 program.
“I’d classify Ava as a thought partner and an analyzer.”
Hortencia Alcazar
Senior Benefits Analyst, Samsung
Endless possibilities for AI-native teams
In addition to the use cases above, the team:
- Built a custom manager support guide for mental health crises in minutes by combining Samsung’s own mental health crisis-response document with materials from Lyra
- Assessed whether their preventative care solution was reducing cardiovascular disease and diabetes and found low engagement among comorbid members who need it most, driving targeted communications
- Explored redesigning the medical plan for next year, including options such as a migration from the OAP to an HDHP, which will inform future negotiations
- and more…
Results
What Carly does for employees
Before Carly, an employee who wrote to the shared service center could wait more than 48 hours for a reply, and often got an answer to only the exact question they had asked. Carly answers in real time, meeting the employee where they are with personalized guidance. 16% of questions come in after hours, when the benefits team isn’t available, meeting an employee at the exact moment they need support.
It also prompts the right next step. For example, when an employee asks about mental health coverage under the medical plan, Carly also points them to Lyra, the path the team wants people to take first. Every employee question becomes a chance to drive awareness of the benefit they should be using, at the moment they need it. In the last four months alone (February – May), Carly instantly and accurately answered over 1,500 employee questions, saving the benefits team approximately 930 hours.
Open enrollment, when question volume is highest, was a key point in the year to prove Carly’s efficacy and impact. According to Sarah Schutzberger, “It was the smoothest open enrollment we’ve ever had. The amount of time it saved our team was extraordinary.”
“Avante is transforming our employees’ experience, is giving our benefits team time back, and has yielded insights resulting in impactful interventions, which are having a positive impact on the health and wellbeing of our team.”
Kevin O’Connell
Senior Director, Total Rewards & HR Operations, Samsung
Screens are illustrative. Names and data shown are fictional to protect user privacy.
How the work itself changed
With Carly fielding the day-to-day employee questions, the team reclaimed the hours it once lost to repetitive inbox support and redirected them to strategy and program development.
The team spends that reclaimed time with Ava, now its first stop for any question, communication, or decision. They use Ava to answer real-time questions in a standing Friday meeting with leadership and bring it to events to pressure-test ideas on the spot.
Ava gives them more strategic insight, faster, and it’s backed by data they trust. In its first few months, the team reclaimed hundreds of hours using Ava to build leadership and employee-facing deliverables and run dozens of cross-source claims analyses that used to take weeks by hand, or days waiting on vendors. That level of visibility and ownership also changes what gets approved. Walking into leadership with the data and the reasoning behind a recommendation moves more initiatives forward, and gives the team the confidence to put program and plan redesign recommendations on the table.
“It’s easier to push things through leadership when you have the data and the why behind the strategy.”
Sarah Schutzberger
Benefits and HR Operations Sr Manager, Samsung
“I don’t know what I did before Ava.”
Cara Ayala, RD, CPT, CHC
Wellness and Benefits, Associate Manager, Samsung
Look ahead
For Samsung, these are the early innings. On the roadmap: bringing their own drug-utilization data to PBM negotiations; connecting LOA, short-term disability, Lyra, and medical claims to forecast and prevent leaves; and next year’s medical plan design.
Benefits clarity for employees and HR
Samsung Semiconductor runs a generous benefits program, including several point solutions, focused on emotional, social, financial, and physical health and wellness for their employees and dependents.
“If you don’t have AI on your benefits team, you’re already behind. Especially in our industry, our employees are so used to using AI in everything they do, from coding to drafting. It’s everywhere. If we don’t have it, how can we stay aligned with the technology and the experience they’re already used to?”