Overview
Leapfrog’s Healthcare AI Accelerator: GenAI / Agentic AI Launchpad POC is a 4–8 week fixed-scope engagement for providers, payors, and healthtech companies that want to validate a high-value GenAI or agentic AI use case with a working proof of concept on AWS.
We design and implement a focused POC using real workflows, real data, and practical healthcare integrations across scenarios such as referral and MedRec intake, patient outreach, chart summarization, claims support, or contact center operations. Depending on the use case, we leverage AWS technologies such as Amazon Bedrock for foundation model access, RAG, and orchestration, Amazon Bedrock AgentCore for agentic workflow patterns and controls, and Nova Sonic+Amazon Connect for IVR.
The goal is to generate real evidence of value while addressing healthcare requirements such as PHI handling, human-in-the-loop workflows, auditability, and workflow safety.
Deliverables:
- A working GenAI and agentic AI POC that proves readiness with real integrations, security guardrails, and measurable results.
- An architecture blueprint and roadmap needed to make a confident go/no-go decision for pilot and production.
- Defined success metrics, including quality and safety thresholds, KPIs, and operational impact aligned to provider and payer workflows.
Why Leapfrog: Leapfrog Technology is an AWS Advanced Tier and AI Competency Partner with deep healthcare and AI delivery experience. We have helped build more than 150 healthcare solutions and bring practical expertise in designing secure, scalable GenAI and agentic AI systems for providers, payors, and healthtech companies on AWS.
Highlights
- Build a working healthcare AI POC in weeks, not months. Validate a prioritized GenAI / agentic AI use case with real workflows, real data, and practical AWS integrations.
- Test value with HIPAA-aware guardrails. Evaluate business impact, workflow fit, PHI handling, human review points, and operational risk in a healthcare-ready POC design.
- Create a clear path from POC to pilot or production. Leave with a working proof of concept, defined success metrics, and a roadmap for scaling on AWS with security and compliance in mind.
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