Data Infrastructure
for Autonomous Healthcare
We are an applied AI research lab focused on improving frontier models for solving clinically and economically meaningful healthcare tasks
For Researchers & AI Labs
We develop high-quality RL environments, evals, and datasets grounded in real-world healthcare data for frontier researchers.
Research
Read the latest benchmarks, papers, and writing on improving AI agents for real-world healthcare environments to which our team has contributed.
May 2026Publication
MEDS: An emerging data standard and ecosystem for health AI research
NEJM AI 2026↗
Apr 2026Benchmark
HealthAdminBench: Can AI agents handle your insurance?
ICLR 2026 Workshop→
Apr 2026Blog
Towards the Autonomous Hospital
Kinetic Systems Team→
May 2025Benchmark
MedHELM: Holistic evaluation of large language models for medical tasks
Nature Medicine 2026↗
Apr 2025Publication
Context Clues: Evaluating long-context models on EHR data
ICLR 2025↗
Mar 2025Benchmark
Top of the CLASS: Benchmarking LLM agents on real-world enterprise tasks
ICLR 2025 Workshop↗
Jan 2025Publication
Zero-shot clinical trial patient matching with large language models
NEJM AI 2025↗
May 2024Publication
Automating the enterprise with foundation models
VLDB 2024↗
Feb 2024Benchmark
MedAlign: A clinician-generated dataset for instruction following with EHRs
AAAI 2024↗
Dec 2023Benchmark
EHRSHOT: An EHR benchmark for few-shot evaluation of foundation models
NeurIPS 2023↗
Nov 2023Benchmark
INSPECT: A multimodal dataset for patient outcome prediction
NeurIPS 2023↗
Oct 2023Publication
The shaky foundations of large language models for electronic health records
npj Digital Medicine 2023↗
Our team builds on a decade of healthcare AI research at Stanford University
Kinetic was founded by PhD researchers behind leading publications on clinical foundation models, privacy-preserving healthcare benchmarks, and LLM-based workflow capture.
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Join us in our mission to help patients and providers
We are a small team of researchers and engineers in San Francisco, working alongside clinicians and frontier labs to advance the field of AI in healthcare