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Keebler Health Tech Stack
AI-powered risk adjustment platform for Medicare & Medicaid providers and payers
Keebler Health builds transformer-based AI models to identify risk adjustment opportunities in healthcare claims—targeting providers and payers managing Medicare and Medicaid populations. The stack reveals a data-heavy architecture (Redshift Serverless, dbt, SQL, Python, FHIR/HL7) paired with active investment in RAG systems and fine-tuned LLMs, suggesting the core product is evolving from rule-based claim analysis toward conversational AI over healthcare knowledge bases. Leadership-tier hires (2 directors, 4 seniors) across a 11–50-person org indicate a push to scale customer implementations and data infrastructure.
Tech Stack 10 technologies
AdoptingRAG
What Keebler Health Is Building
◆Challenges
- Scale across high-profile healthcare organizations
- Ensuring compliance with hipaa
- Long-running stateful healthcare processes
- Performance and cost efficiency
- Providers in value-based care environments
- Implementing for new partners
- Streamline vbc workflows
- Improving speed, quality, and scalability
- Identifying implementation risks
- Optimizing data infrastructure for healthcare ai solutions
▲Active Projects
- End-to-end implementation lifecycle for newly signed customers
- Data infrastructure for healthcare ai solutions
- Data warehousing with redshift serverless
- Fine-tune llms for healthcare applications
- Implement rag systems for knowledge retrieval
- New high-impact product line
- Value-based care workflow platform
- Repeatable implementation patterns, tooling, and best practices
- Customer-specific solution design
- Repeatable implementation patterns
Hiring Activity
Minimal10 roles · 0 in 30d
Department
Seniority
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