Seqera Platform Enterprise 26.1 delivers new AI capabilities, smarter compute, expanded data integrations, and improved GxP-readiness. Whether you're scaling bioinformatics across new teams, tightening governance in regulated environments, or reducing cloud spend, this release will help your organization operate with greater speed, efficiency, and confidence.
AI for Scientists
Seqera Co-Scientist
Seqera Co-Scientist is the intelligent, collaborative partner that brings the full power of Seqera to all scientists. Co-Scientist understands scientific context and executes with intelligence, making the bioinformatics more accessible across your organization. Built for Enterprise, Co-Scientist integrates deeply with your data, compute, and internally hosted models, providing complete visibility across your bioinformatics stack without compromising on reproducibility or security. Key capabilities include:
- →Self-Service Interface for Scientists: Enable bench scientists to launch pipelines, manage data, and explore results independently in a simplified portal controlled by administrators.
- →Interactive Research Intelligence: Build, validate, optimize, and debug pipelines through CLI, IDE, MCP, or web with full workspace context, working alongside internal AI tools and LLMs.
- →Automation with Agents (Coming Soon): Trigger pipelines, detect and self-fix failures, and autonomously improve code with 24/7 agents. Always on, always working.
Benchling Integration
Bioinformatics is a critical piece of the R&D knowledge graph. Through Benchling's AI Connectors, your teams can now integrate Seqera into Benchling via Seqera MCP. Scientists can launch and track Nextflow pipelines, investigate results, and spin up Studios environments, all without leaving Benchling. This ensures pipeline results connect back to the samples and people that generated them and the bioinformatics team can continue to ensure reproducibility and access control while democratizing access.
Smarter Compute
Seqera Intelligent Compute
Seqera Intelligent Compute is a new way to orchestrate Nextflow that continuously optimizes resource allocation, learns from previous runs, and automatically recovers from failures, all without manual configuration from your team. Intelligent Compute dynamically profiles tasks, packing them onto right-sized machines, and selecting optimal architectures at execution time. In benchmarks against AWS Batch, Intelligent Compute delivered RNASeq results at <$2/sample – reducing CPU hours by 19%, cutting costs by over 50%, and improving turnaround times by up to 57%.
Cross-Cloud Compute
This release brings significant improvements to compute environments across all three major cloud providers, strengthening security, flexibility, and management controls. This includes new credential modes, network controls, and the ability to disable compute environments. Provider-specific highlights include:
- →AWS: New credential modes with support for key-based and role-based. Added AWS External ID support for role-based credentials.
- →Azure: Separate head and worker pool support, VNet and subnet controls, managed identity support, and Entra service principal credentials.
- →GCP: Workload Identity Federation (WIF) credential support, network tagging, boot disk image selection, multiple machine type support, and configurable retry behavior for Google Batch.
Data and Pipeline Management
Native Data Lineage
Nextflow data lineage now surfaces this full provenance chain directly in Seqera, attached to both pipeline runs and objects in Data Explorer. Your teams can trace any file's provenance end-to-end without leaving the platform, enabling faster debugging, easier audits, and broader access to run history. For organizations in regulated industries, it directly supports compliance and data integrity requirements.
Data Explorer Improvements
We’ve expanded Data Explorer’s format support and usability, making it easier to explore and interact with scientific data directly within platform.
- →IGV and Mol* - Native visualization of genomic alignments and 3D molecular structures.
- →Improved file views - Extensible view modes for JSON, IGV, and plain text files.
- →Fusion symlinks - Resolution of Fusion symlinks through Data Explorer API.
- →Linked datasets: Reference externally hosted data via URL without duplication.
Trust and Compliance
Full GxP Offering
Seqera now provides full GxP offerings, enabling your teams to run validated bioinformatics pipelines in regulated environments. Our approach combines Seqera’s enterprise architecture with proven bioinformatics expertise to deliver secure, traceable, and scalable analysis aligned with FDA and EMA expectations. Teams can maintain velocity while meeting compliance requirements, with full traceability from research through clinical and manufacturing environments. Two packages are available:
- →GxP Documentation - Compliance foundation, audits / traceability, validation documentation.
- →GxP Validation - Includes validation documentation, test evidence, GAMP5-alignment.
Identity Integration
Seqera supports delegating workspace and team membership to your identity provider (IdP). Link a team to an IdP group and membership is evaluated automatically at every SSO login, with users added or removed based on their group claims. Workspace and role assignments remain under your control, so the IdP owns membership while your organization owns access policy. This eliminates onboarding lag and access drift, ensuring the right people have the right access from the moment they log in.
GitHub App Support
As an alternative to personal access tokens, Seqera now supports GitHub App authentication. GitHub Apps use short-lived tokens and fine-grained permissions scoped to specific repositories, independent of individual user accounts. A built-in manifest flow lets you create and install a GitHub App directly from Seqera, eliminating manual secret management. For teams enforcing strict access controls around pipeline code and shared repositories, this provides a more secure and auditable integration with GitHub.
Looking ahead
This release broadens and strengthens the foundations that matter most at scale: AI-assisted development, smarter compute, expanded cloud infrastructure, richer data management, and deeper compliance. In the releases ahead, expect continued investment in autonomous agents, expanded cloud provider support, and tighter integration with the tools your scientists already rely on.