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Medra builds a platform that speeds scientific research by automating lab work with AI and robotics. Its Continuous Science Platform has two parts: Physical AI, which uses general-purpose robots to perform lab tasks (like pipetting and handling samples) and connect with standard instruments, and Scientific AI, which analyzes experimental data to find patterns and suggest new experiments, creating a closed loop that learns from results. Scientists can give workflows in natural language, and the system runs experiments at a larger scale and faster pace than manual work. Medra differentiates itself by tightly integrating flexible robotic automation with AI-driven experiment design in a continuous feedback loop, supported by partnerships with biopharma and research organizations. Its goal is to remove data bottlenecks in biology and drug discovery by enabling rapid, high-throughput, automated laboratories.
Industries
Data & Analytics
Robotics & Automation
AI & Machine Learning
Biotechnology
Company Size
51-200
Company Stage
Series A
Total Funding
$63M
Headquarters
San Francisco, California
Founded
2021
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Total Funding
$63M
Above
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Funded Over
2 Rounds
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Remote Work Options
Paid Vacation
Telework not specified
Flexible Work Hours
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Employee Referral Bonus
Paid Holidays
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Medra launches AI Experimentalist and announces DARPA collaboration. June 26, 2026 Press play to listen to this content DARPA-funded effort will use Medra's new scientific reasoning layer inside ML001, the company's flagship autonomous science lab SAN FRANCISCO, June 26, 2026 - Medra has launched the AI Experimentalist, the scientific reasoning layer of its Physical AI Scientist Platform, and announced a project funded by the Defense Advanced Research Projects Agency (DARPA). As part of this DARPA-funded project, Medra is advancing its platform's capabilities to translate natural-language scientific goals and human-written protocols into machine-executable experiments that can be measured, learned from, and improved over time. DARPA is an independent research and development agency within the U.S. Department of Defense responsible for breakthrough technologies for national security. Scientists can specify high-level research objectives, and Medra's AI Experimentalist translates them into executable experimental plans. Unlike AI tools that focus on a single stage of the scientific workflow, the AI Experimentalist spans the full experimental cycle: from reviewing literature and designing experiments to coordinating wet-lab execution, analyzing results, and refining protocols for subsequent runs. By closing the loop between planning, execution, and learning, it enables experiments to be carried out with minimal human intervention while keeping scientists in control of research goals. The AI Experimentalist works in concert with Medra's Physical AI Lab, a wet-lab execution layer. Together they form the Physical AI Scientist platform, a closed-loop system that tightly couples scientific reasoning and experimentation. With a model-agnostic agentic harness and a multi-agent architecture, the platform can incorporate frontier AI capabilities alongside scientific agents and prediction models. Partners can access Medra's AI Experimentalist through Physical AI Labs deployed on site at customer facilities or operated remotely through Medra Lab 001 (ML001), Medra's flagship autonomous science laboratory. Built in 77 days and opened in April 2026, select closed-beta projects are now live across academia, biopharma, and government, including DARPA. ML001 is currently running and developing assays in antibody discovery, protein engineering, gene editing, and cell biology. "With frontier models becoming increasingly capable of predicting novel molecules and generating scientific hypotheses, the bottleneck in science is shifting toward the ability to validate those predictions," said Michelle Lee, founder and CEO of Medra. "But running experiments is not just about robotic execution. Assay development and parameter tuning often take months of experimentation and refinement. The AI Experimentalist enables autonomous, end-to-end experimental design with a Physical AI lab in the loop." About Medra Medra is building the Physical AI Scientist, a closed-loop system that tightly integrates AI scientific reasoning and experimentation. Founded in 2022, Medra has raised over $60M from investors including Human Capital, Lux Capital, Menlo Ventures, Catalio Capital, Neo, 776, and Fusion Fund. Medra launched ML001 in San Francisco as the largest autonomous lab in the U.S. Most quantum computing announcements revolve around hardware: more qubits, new processors, and better error correction... Nvidia this week highlighted an early deployment of its Vera CPU at Los Alamos National... After tracking quantum computing for years, Intersect360 Research says the market has matured enough to... The world spent more than $300 billion on AI data centers in 2025, representing a... As previously noted, the Seventh National Research Platform (7NRP) workshop was held in La Jolla,... A recent paper submitted to ArXiv by famed HPC scientist Satoshi Matsuoka, Director of the...
Medra, an autonomous science company, has launched its AI Experimentalist and announced a collaboration with the Defense Advanced Research Projects Agency. The AI Experimentalist translates natural-language scientific goals into machine-executable experiments across the full experimental cycle, from literature review to protocol refinement. The system works alongside Medra's Physical AI Lab to form a closed-loop platform. Partners can access the technology through on-site deployments or remotely via Medra Lab 001, the company's flagship autonomous laboratory in San Francisco, which opened in April 2026 after 77 days of construction. The facility is running projects across academia, biopharma and government in antibody discovery, protein engineering, gene editing and cell biology. Founded in 2022, Medra has raised over $60 million from investors including Human Capital, Lux Capital and Menlo Ventures.
Medra has raised $52 million to build a 38,000-square-foot autonomous robot laboratory in the Bay Area, bringing total funding to $63 million. The round was led by Human Capital. The startup develops software enabling scientists to direct laboratory robots using everyday language, similar to ChatGPT. The robots conduct drug research around the clock for partners including Genentech and Addition Therapeutics, logging every experimental detail to train AI models. Founded in 2022 by Stanford robotics PhD Michelle Lee, Medra currently has five paid installations across the United States. The new facility, built in 90 days, will house hundreds of robots generating experimental data to improve AI models for scientific research. The system can operate over 75% of instruments used in laboratories today.
Medra founder & CEO Michelle Lee (ex-Stanford AI Lab, Nvidia, SpaceX) announces the opening of America's largest autonomous laboratory, featuring hundreds of robots running experiments with zero human intervention. Mission: eradicate disease through AI-powered robotic lab automation.
Medra, a robotics and AI startup founded by Stanford PhD Michelle Lee, has raised $11 million in early funding to automate scientific laboratory work. The company is developing robots and software that can interact with standard lab equipment by reading screens, pressing buttons and handling physical tasks currently performed by human technicians. Unlike traditional lab robotics that work with limited instruments, Medra's platform combines AI with robotics to adapt to new equipment and workflows autonomously. The technology aims to move beyond pre-programmed sequences to perform a broader range of routine experiments and data collection tasks. Early interest from biotech companies indicates demand for solutions that reduce manual labour and accelerate research. The startup's approach integrates AI directly into experimental workflows, potentially shortening research timelines whilst allowing scientists to focus on higher-level problems.
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Industries
Data & Analytics
Robotics & Automation
AI & Machine Learning
Biotechnology
Company Size
51-200
Company Stage
Series A
Total Funding
$63M
Headquarters
San Francisco, California
Founded
2021
Find jobs on Simplify and start your career today