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Hippocratic AI Tech Stack

Safety-focused LLM purpose-built for healthcare delivery and clinical workflows

Hospitals and Health Care Palo Alto, California 51–200 employees Founded 2023 Privately Held
hippocraticai.com LinkedIn

Hippocratic AI builds a healthcare-specific large language model designed around clinical safety. The stack reveals heavy investment in both healthcare data standards (Epic, Cerner, Athena, HL7, FHIR) and ML infrastructure (PyTorch, CUDA, RLHF), with active adoption of retrieval-augmented generation (RAG) pipelines. The hiring mix — engineering-heavy (30 roles), paired with dedicated support (20) and healthcare domain roles (4) — signals a go-to-market strategy centered on complex health-system deployments and clinical integration rather than self-serve adoption.

Tech Stack 63 technologies

Core StackEpic Systems Python C++ PyTorch Rippling Flask Django PostgreSQL Redis Grafana RAG Unix ESPNET Kaldi CUDA HL7 v2 FHIR Cerner Athena Spring Boot RLHF Locust k6 Gatling JMeter Mirth Rhapsody InterSystems IRIS Streamlit Gradio+33 more
AdoptingRAG

What Hippocratic AI Is Building

◆Challenges

  • Implementing ai solutions in clinical workflows
  • Scaling customer success
  • Deploying llm safely and efficiently
  • Adoption across complex health system environments
  • Deploying llm safely in healthcare
  • Building safe autonomous clinical conversations
  • Meeting client credentialing requirements
  • Regulatory compliance for ai interactions
  • Burnout
  • Cost efficiency improvement

▲Active Projects

  • Rag pipelines and multi-agent workflows
  • Enterprise implementations of hippocratic ai solutions
  • Implementing ai solutions in nursing workflows
  • Best practices for onboarding and workflow integration
  • Voice-based generative healthcare agents
  • Healthcare data integration pipelines
  • Build playbooks and processes for cs model
  • Reusable integration patterns
  • Product implementation for nursing workflows
  • Llm deployment in healthcare

Hiring Activity

Accelerating75 roles · 60 in 30d

Department

Engineering
30
Support
20
Sales
5
Healthcare
4
Executive
2
Finance
2
HR
2
Legal
2

Seniority

Senior
44
Mid
9
VP
9
Director
6
Lead
2
Staff
2
Junior
1
Principal
1

Notable leadership hires: Chief Nursing Officer

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About Hippocratic AI

Hippocratic AI develops a large language model specifically engineered for healthcare provider organizations. The company targets hospital systems and health networks with solutions spanning clinical documentation, nursing workflows, and patient-facing generative agents. Founded in 2023 and based in Palo Alto, the organization operates across 51–200 employees, concentrated in the United States. Core infrastructure sits on industry-standard EHR platforms (Epic, Cerner, Athena) and healthcare interoperability standards (HL7, FHIR), paired with modern ML deployment tools (PyTorch, CUDA, Streamlit, Grafana). Active projects center on enterprise implementations, nursing workflow integration, voice-based agents, and healthcare data pipeline architecture — reflecting a focus on regulated, multi-stakeholder healthcare environments where safety and integration depth matter more than speed to deployment.

HeadquartersPalo Alto, California
Company Size51–200 employees
Founded2023
Hiring MarketsUnited States

Frequently Asked Questions

What is Hippocratic AI's tech stack?

Hippocratic AI uses Epic Systems, Cerner, Athena, HL7 v2, and FHIR for EHR integration; PyTorch, CUDA, and RLHF for model development; Python, C++, Flask, and Django for backend services; and Grafana, PostgreSQL, Redis for infrastructure. RAG pipelines are actively in development.

What is Hippocratic AI working on?

Current projects include RAG pipelines and multi-agent workflows, enterprise implementations across health systems, nursing workflow integration, voice-based clinical agents, healthcare data pipelines, and LLM deployment safety best practices for complex regulatory environments.

How this profile is built

Hippocratic AI's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.