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Company description

Nygen is an AI-native platform purpose-built for single-cell omics interpretation, designed to help research teams move from raw single-cell data to decision-ready biological insight through clear, reproducible workflows. The platform serves researchers across drug discovery, biomarker identification, translational science, clinical trials, cell therapy, and toxicology, powering discovery at leading research institutions worldwide.

Rather than simply describing single-cell data, Nygen pushes programs into genuine discovery by surfacing biology that conventional workflows miss and translating it into insight that is traceable, auditable, and actionable. The company's technology spans computation, annotation, and interpretation, built on the conviction that single-cell omics will solve problems that have stalled drug discovery for decades.

Core Products

• CyteType (Flagship — Reasoning Engine): A structured AI reasoning system that assigns cell identity the way a domain expert would. CyteType delivers confidence-scored, evidence-backed, fully auditable cell characterization of single-cell RNA-seq data, including annotation evidence, confidence scores, and cell state summaries. It is capable of identifying complex cell states such as SPEM cells, fetal mesenchymal progenitors, cancer-associated fibroblasts, and activated lipid-secretory enterocytes, with supporting and missing marker gene coverage clearly reported.
• ScarfWeb (GUI Workbench): A distributed, secure infrastructure for intuitive secondary analysis delivered entirely browser-native, enabling collaborative exploration of single-cell datasets without local installation requirements.

Key Capabilities and Use Cases

• Resolves state-level cell identity with structured evidence, distinguishing disease drivers from bystanders rather than collapsing cell states into broad labels.
• Identifies druggable targets with genuine cell-type specificity, addressing the analytical depth that standard workflows rarely deliver.
• Surfaces rare or transient cell populations that are frequently missed by conventional pipelines.
• Assesses whether candidate targets are selective enough to support a therapeutic window.
• Provides multi-perspective biological reasoning, including mesenchymal, developmental, and computational biology viewpoints, with confidence and heterogeneity scoring per cluster.
• Supports rapid and scalable analysis through cloud infrastructure spanning 22 AWS regions, with no queues or pipeline bottlenecks.

Security, Compliance, and Data Governance

• SOC 2 Compliant: Verified controls for security, availability, and confidentiality.
• ISO 27001 Certified: Full information security management system certification.
• Zero Data Retention: An option for zero data retention is available, with deletion within one hour, configurable per account.
• Data Residency: Geographic region selection for data processing and storage.
• LLM Provider Agreements: Data Processing Agreements and Zero Data Retention contracts in place with both OpenAI and Anthropic.
• Data Transmission: Only pseudo-bulk expression data is transmitted to servers, with a local SDK option also available.
• Access Control: Password-protected reports and role-based access controls within organizations.

Notable Partnerships and Recognition

• Nygen Analytics partnered with VLP Therapeutics on a Vinnova-funded cancer immunotherapy research initiative, receiving a 1M SEK grant to develop AI-powered predictive models.
• The company has published research on multi-agent AI enabling evidence-based cell annotation in single-cell transcriptomics.
• Nygen participates in the broader computational biology community, including events such as the Glasgow Computational Biology Community Event.

Nygen is positioned as the interpretation layer that sits above raw single-cell analysis, making it particularly relevant for life sciences teams that need to move beyond descriptive outputs toward biology they can act on with confidence.

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Software attributed to Nygen Analytics

• CyteTypeView
• ScarfWebView

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