AI platform embedding clinical protocols into hospital workflows
C8 Health builds AI-powered software that embeds vetted clinical protocols directly into how doctors work—reducing the friction between best-practice guidelines and real-time patient care. The tech stack reveals a dual engineering focus: modern web/mobile infrastructure (React, Angular, Vue, Node.js, Python on AWS/GCP/Azure) paired with LLM tooling (LangChain, LlamaIndex) for retrieval-augmented generation and agentic document understanding. Active projects around RAG architecture, prompt strategy, and agentic systems signal the company is moving beyond simple protocol lookup toward AI agents that reason over clinical knowledge—a shift from decision-support toward AI-driven clinical automation.
C8 Health operates a platform for US hospital systems that surfaces clinical best practices at the point of care—in clinician workflows, when decisions happen. The product integrates locally vetted protocols into EHR-adjacent surfaces and decision moments, combining knowledge management with AI to reduce care inconsistency and improve protocol adherence. The company works with over 100 hospitals across the United States. The engineering and product focus (5 of 10 active roles) reflects a maturation phase: moving from initial customer implementations toward platform scalability and AI-driven inference, while customer success and support roles indicate a sales-assisted go-to-market where onboarding complexity remains a material pain point.
Frontend: React, Angular, Vue, TypeScript. Backend: Node.js, Python, Java. Infrastructure: AWS, GCP, Azure, Docker, Kubernetes. AI: LangChain, LlamaIndex for RAG. Data/BI: MongoDB, Salesforce, Tableau, Looker. Testing: Selenium, Playwright, Cypress, Detox. CI/CD: Jenkins, GitLab, GitHub Actions.
Core focus: retrieval-augmented generation (RAG) architecture, agentic AI for document understanding, LLM prompt strategy, and scalable onboarding. Also building event-driven outreach and high-performance outbound playbook engines.
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