Technology conceived to reveal deeper biology

Built and validated today

Patented algorithms, peer-reviewed tools, and structured reasoning. Every layer we ship makes the next one possible.

Algorithms

TopACeDO / RGS

Patented subsampling that preserves rare cell states. Enables industrial-scale annotation at 6–7x lower cost.

We built proprietary subsampling and graph reconstruction methods that let us iterate on product at a pace our infrastructure costs shouldn't allow. These efficiency layers sit underneath everything we ship. They are why we can do things at scale that others budget for but don't attempt.

Patented Nature Comms
GUI Workbench

ScarfWeb

Distributed, secure infrastructure for secondary analysis, browser-native.

Published in Nature Communications. Up to 100x more memory-efficient than existing tools. We took the computational foundation and built a visual analysis environment on top of it, because single-cell biology shouldn't require a bioinformatics degree to interpret.

No-code Up to 100x memory efficiency
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Reasoning Engine

CyteType

Multi-agent AI for evidence-based cell characterisation and drug discovery. Annotation, target assessment, and interactive exploration with full audit trails.

Five specialized agents evaluate every cluster independently: identity, confidence, evidence for and against, functional context, literature validation. Validated across 977 clusters, 20 datasets, 16 language models. The architecture outperforms every existing method.

Up-to 388% accuracy Auditable trail
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Building toward better discovery

Our technology is built from the ground up so that every new layer makes better discovery possible. These are what we are working on next.

Augmented Data

Disease-scale atlases

Disease-focused cell atlases with deep biological reasoning. CyteType-annotated at industrial scale across 500M+ cells.

We are applying our reasoning engine across large-scale public single-cell corpora to build disease-focused atlases with structured biological reasoning at every cluster. Not labels. Reasoning chains: what each population is, what it isn't, why, and what it means.

500M+ cells Structured reasoning data
Foundation Model

Deployable foundation model

Structured biological reasoning distilled into a single deployable model. Runs on any GPU, no external LLMs, no internet required.

Purpose-built foundation models trained on structured biological reasoning, not expression-to-label mappings. Models that internalize why cells are what they are. Designed to be fine-tuned for specific disease areas, specific workflows, specific teams.

Fine-tunable On-premise
Purpose-Tuned Models

Pharma-ready AI

Configured for specific pharma workflows and fine-tuned on proprietary data. One model per team, deployed on-prem, no data leaves the firewall.

Each pharma team asks different questions and needs the model to behave differently. Discovery, cell therapy, safety, toxicology. Purpose-tuned models adapt through prompt tuning and optional fine-tuning on proprietary data.

Cell state detection Off-target detection TargetID Cross-cohort analysis

Your data has more to say.

Talk to our team about how Nygen can fit into your single-cell discovery workflow.

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