A future where scientific breakthroughs are no longer bottlenecked by the tools used to pursue them.
Biology is moving faster than ever. Models can now predict protein structures in seconds, simulate molecular interactions at scale, and surface patterns across datasets no human team could process alone. Yet many research teams still stitch together fragmented tools, manage compute overhead, and rebuild workflows from scratch for each new question. The bottleneck is no longer ideas. It is infrastructure.
A researcher should not have to wait on tooling to test a hypothesis. They should not lose a week to environment setup, compute configuration, or workflow duplication. We believe the distance between asking a question and seeing what the data shows should be as short as possible. Closing that gap is one of the highest leverage investments we can make in scientific progress.
Fastfold is built on the conviction that the best science happens when human judgment and machine capability are deeply integrated. We are building a framework for collaboration where scientists and agents plan, execute, analyze, and iterate together. Agents can autonomously handle well defined tasks so economically valuable work is completed by humans and agents together, with higher quality decisions and faster discovery.
Science that cannot be reproduced cannot compound. Every workflow on Fastfold is traceable. Every run is versioned. Every result is shareable in a way that lets teams understand, challenge, and build on each other's work.
The future of biotech software is composable research systems where models, datasets, compute, and agents work together in architectures teams can audit, evolve, and trust over time. We are building the infrastructure layer for that future so institutional knowledge lives in systems that learn, persist, and scale.
We are building for scientists working on the hardest problems in biology and medicine. Fastfold exists to give every research team, regardless of size or resources, the infrastructure to increase productivity, reduce operational friction, and spend more time on the most valuable scientific tasks this moment in science demands.
— By the Fastfold team