Learn without labels
Find the latent patterns in your images before you know what to call them.
Representation learning for cell imaging
Percolatech turns raw cell images into a biological map your team can search, compare, and build on — without hand-labeling every phenotype.
RAW PIXELS → BIOLOGICAL SIGNAL
Cell imaging holds the record of what your biology is doing. But today, most teams only inspect a sliver of it — after weeks of manual annotation and brittle analysis.
Percolatech learns directly from your image collections. The result is a high-dimensional representation that makes subtle cell states measurable, comparable, and reusable across every experiment.
Explore the platform ↘Find the latent patterns in your images before you know what to call them.
Quantify treatment response, morphology, and state transitions in one shared space.
Build a continuously more valuable representation of your biology, not another silo.
From pixels to possibility
Built for the reality of modern cell biology: messy images, evolving questions, and science that can’t wait for perfect labels.
Upload a plate, point to your cloud bucket, or integrate your imaging pipeline.
OME-TIFF · PNG · JPG · HCSOur models build a robust representation of morphology, structure, and cell state.
SELF-SUPERVISED · MULTI-SCALESurface novel phenotypes, compare conditions, and export features to your stack.
SEARCH · CLUSTER · PREDICTBuilt for discovery teams
PHENOTYPIC SCREENING
PERTURBATION BIOLOGY
MODEL DEVELOPMENT
A representation you own
Percolatech is designed to become a quiet, powerful layer in your research stack — giving your team a durable way to learn from visual biology.
Not another black box
Browse any experiment by visual similarity, surface outliers, and turn the clusters you find into a shared biological vocabulary.
Take embeddings, per-cell features, and condition-level summaries into your notebooks, LIMS, or downstream machine-learning workflows.
Trace every signal back to the image evidence so scientists can validate, prioritize, and communicate what the model has found.
Straightforward plans
Every plan includes our self-supervised cell representation engine, a private workspace, and scientist-led onboarding. Start with the image volume you have today.
EXPLORE
billed annually
Start with ExploreDISCOVER
billed annually
Choose DiscoverFOUNDATION
annual platform agreement
Talk to our teamNeed a proof-of-value first? We run a 30-day pilot on one of your real assays. Plan a pilot.
Built for sensitive science
Percolatech was designed for teams working with valuable, pre-publication biology. You decide who can access a workspace, what gets exported, and where your image data lives.
Talk to security ↗Your images and derived representations are isolated from every other customer workspace.
Role-based access, audit trails, and SSO are available on Foundation.
Use our managed cloud or keep data inside your approved cloud environment.
Questions, answered
We support common microscopy image formats including OME-TIFF, TIFF, PNG, and JPEG. During onboarding, we help map channels and plate metadata so your assay is ready to learn from.
No. Percolatech learns directly from image structure, morphology, and variation. Labels and assay metadata can be added later to test hypotheses or train targeted classifiers.
A focused pilot can begin as soon as we receive a representative assay and its metadata. Most teams have a first searchable representation within days, not months.
Yes. Foundation includes private-cloud and VPC deployment options for organizations with specific data residency or security requirements.
The frontier is already in your images
Bring us one assay and one question. We’ll show you what a learnable representation can uncover.
Plan your pilot ↗