Claymore
Claymore is an autonomous experimentation platform that gives scientific laboratories a persistent intelligence layer capable of conducting research on their behalf.
Core trick
An agent reads lab results, updates its state, and sends next-step protocols to Opentrons and PyLabRobot liquid-handling robots in a closed loop.
Description
Claymore is an autonomous experimentation platform that gives scientific laboratories a persistent intelligence layer capable of conducting research on their behalf. Rather than acting as another chat interface or analysis tool, Claymore understands a lab's collective knowledge and can directly carry out scientific research in both computational environments and the physical world.
Claymore can autonomously perform computational research through tools such as Claude Science for data analysis, machine learning, and literature review. It can also control laboratory robots through platforms such as Opentrons and PyLabRobot, enabling it to design, validate, and execute physical experiments in the real world—from pipetting reagents across a 96-well plate to coordinating centrifugation and automated measurement. As new evidence is generated, Claymore interprets the results, updates its understanding, and determines the next experiment, creating a continuous closed-loop experimentation cycle.
Scientists cannot work around the clock, but Claymore can. While researchers are focused on other projects, away for the evening, or on vacation, Claymore can keep analyzing data, testing hypotheses, running experiments, and planning the next iteration. It gives scientists back the time they do not have, accelerating discovery by ensuring promising ideas are continuously investigated instead of waiting days, weeks, or indefinitely to be pursued.
README excerpt
# Claymore > **The autonomous intelligence layer for scientific research.** Claymore is an autonomous experimentation platform that enables scientific laboratories to continuously conduct research in both computational environments and the physical world. Rather than acting as another chat interface or analysis tool, Claymore understands a lab's collective knowledge, decides what investigations should be performed, executes computational analyses, controls laboratory robots, and continuously learns from the results. ## The Problem Scientific progress is often limited not by a lack of ideas, but by a lack of time. Every day, researchers propose promising hypotheses in Slack threads, meetings, notebooks, GitHub issues, and emails. Most are never explored—not because they lack merit, but because experiments are expensive, researchers are busy, and priorities constantly shift. Claymore ensures those ideas don't stay forgotten. ## What Claymore Does Claymore acts as a persistent intelligence layer for an entire laboratory. It continuously ingests scientific context from collaboration tools, codebases, protocols, datasets, and experiment records, building a unified understanding of everything a lab has discussed, tested, and learned. From there, it can: * Discover promising hypotheses that were proposed but never investigated. * Plan the most informative next experiment. * Perform computational research through Claude Science, including data analysis, machine learning, s