No data ever leaves your corporate network
Benchmark models on your in-house data
Explore outputs via a GUI or integrate them into existing workflows
Securely customize models to your domain of interests (on own or third-party data)
Optimized for enterprise security and scalability requirements
Designed for scientists ApherisFold is built to supplement rather than replace existing internal pipelines. It scales to many users, models and requests over multiple GPUs, and integrates into enterprise R&D stacks.
Secure local inference
ApherisFold can be deployed locally such that no data leaves the corporate network and internal security policies are met.
In-house model benchmarking
Securely evaluate and compare models on your in-house data using performance guidelines and a benchmarking kit.
Model customization
Securely customize models to your domain of interests, either on your own data or on third-party data via federated data networks.
Visualization and integration
Explore 3D molecular visualization through a scientist-friendly GUI or connect outputs to existing drug discovery workflows programmatically via an API.
Dr. Lukas Pluska
Read Lukas' Co-Folding blog
to find out why co-folding models, such as AlphaFold 3, Boltz‑2, and OpenFold3, show decreased accuracy on novel targets. Learn how to critically assess their applicability domain, and why customizing these models to your own research tasks is essential for achieving meaningful results.
Securely use the latest co-folding models, like OpenFold3 and Boltz-2, on your proprietary data.
Join the waitlist, and we’ll let you know as soon as it’s live.