Healthcare AI Agents. Assembled.
Assemble healthcare AI agents, tools, and clinical context into governed workflows that move from pilot to production.
Healthcare AI is stuck in pilots
That’s not an agent problem. That’s an assembly problem.
Healthcare organizations are experimenting with agents, models, and tools. But most efforts stall before they become reliable, governed workflows.
Fragmented agents
Agents built by different teams do not work together without custom integration.
Lost context
Patient, cohort, policy, and workflow context gets dropped across disconnected tools.
Limited governance
Teams need audit trails, controls, and traceability before AI can support real operations.
Prompt Opinion solves that problem
One platform for assembling healthcare AI workflows
Connect agents, tools, healthcare data, and organizational context into governed workflows.
Connect agents and tools
Ground them in context
Give it standards for interoperability
Assemble workflows and controls
Built on open standards
No lock-in. Any agent. Any model. Any source.
Prompt Opinion uses open standards so that agents, tools, and healthcare data can work together without rebuilding every integration from scratch.
MCP
Connects agents to reusable tools, functions, and external services.
A2A
Enables agents to communicate, delegate, and coordinate across workflows.
HL7 FHIR
Grounds workflows in standardized healthcare data from EHRs, labs, payers, and other systems.
Built for teams creating and deploying healthcare AI
One platform for builders and organizations.
Prompt Opinion connects builders of interoperable agents with organizations ready to assemble and deploy them in real workflows.
For Builders
Create interoperable agents and tools that can be published, discovered, and used across healthcare workflows.
- → Build on MCP, A2A, and FHIR. No custom plumbing
- → Reference implementations in TypeScript and Python
- → Publish once, reach every organization on the platform
Use cases in action
Healthcare AI workflows assembled on Prompt Opinion.
These workflows showcase how agents, tools, healthcare data, and workflow context can be assembled into practical healthcare workflows. Each project highlights a different scenario for clinical coordination, governance, interoperability, automation, or operational decision support.
Together, they show what interoperable infrastructure makes possible in real healthcare workflows.
LookCloser
LookCloser demonstrates how the platform enables builders to create sophisticated multi-agent healthcare AI workflows that extend beyond copilots into operational clinical coordination. The project combines longitudinal reasoning, FHIR-native workflows, intelligent escalation, and agent-to-agent collaboration to solve real-world follow-up challenges in healthcare.
Built by Rifqi Haikal
LoopGuard Passport
LoopGuard Passport demonstrates how the platform can support governed, longitudinal healthcare AI workflows designed to prevent silent diagnostic follow-up failures. The project combines intelligent agents, FHIR-native interoperability, and clinical reasoning to identify unresolved care loops, prioritize risk, and improve clinical coordination without increasing alert fatigue.
Built by Aayush Sigdel
Ctrl+Alt+Heal
Ctrl+Alt+Heal demonstrates how the platform can combine clinical NLP, deterministic reasoning, and FHIR-native workflows to build audit-defensible healthcare AI systems. The project identifies coding gaps, interprets unstructured clinical notes, and surfaces actionable reimbursement insights while maintaining clinical traceability and interoperability.
Built by Kishan Raj Vandhavasi Goutham Kumar & Jaswanth Thundlam
Ready to assemble healthcare AI into real workflows?
Share your use case, and we’ll help you find the right starting point with Prompt Opinion.