Teselagen

TeselaGen is an AI-driven biological R&D platform that deploys specialized autonomous agents to accelerate the Design-Build-Test-Learn (DBTL) cycle for life sciences teams. Through its flagship product, Tesela AI, the platform enables researchers to design DNA libraries, generate assembly protocols, and optimize biomolecules using natural language prompts — delivering results up to 10x faster than conventional approaches. TeselaGen serves a broad range of customers, from individual academic researchers and biotech startups to large pharmaceutical organizations and industrial synthetic biology teams.

Unlike general-purpose chatbots, Tesela AI agents execute real computational algorithms for tasks such as primer design, assembly optimization, and biomolecule engineering. The platform is designed to be platform-agnostic, connecting to existing ELN and LIMS systems, proprietary databases, or TeselaGen's own platform via a REST API and Python SDK.

Core AI Agents

• Library Designer Agent: Designs combinatorial DNA libraries from natural language descriptions, supporting assembly methods including Golden Gate, Gibson, and MoClo. Capable of generating up to 384-variant libraries in minutes, complete with primer design, junction design, plate maps, and automation worklists.
• Library Construction Optimizer: Automatically generates complete assembly protocols including primer design, plate maps, thermocycler programs, and liquid-handling worklists compatible with any automation platform. Produces assembly-ready protocols rather than sequences alone.
• Experiment Optimizer: Powered by Synthetic Evolution®, TeselaGen's patented machine learning engine, this agent closes DBTL cycles 10x faster than random screening approaches by intelligently guiding experimental design and iteration.

Key Capabilities and Performance

• 7x increase in design and build speed for biological R&D workflows
• 10x reduction in development costs
• 2x increase in production rate and titer for bioprocess optimization
• Natural language-driven interface for initiating complex library design and sequence optimization tasks
• Support for protein sequence optimization using protein modeling tools, accessible via conversational prompts
• Patented Synthetic Evolution® ML engine for accelerated iterative optimization

Integrations and Compatibility

• ELN integrations: Benchling, SnapGene, and any ELN/LIMS via open API
• Automation platforms: Tecan, Hamilton, Biomek, Echo Acoustic, Mantis dispensing, QPix colony picking
• DNA synthesis providers: Twist Bioscience, IDT
• Databases: GenBank, UniProt
• Analytics: BioLector
• Developer access via Python SDK and REST API

Deployment and Pricing Tiers

• Community (Free): Designed for individual researchers and students; includes access to basic agents, simple library design and protocol generation, Python SDK and REST API access, and community support.
• Starter ($150/month per user): Targeted at biotech startups and research groups; includes 10x more agent tokens per month, ELN and LIMS connectors, extended agent and tool access, and team collaboration features.
• Enterprise (Custom pricing): Built for pharma and large biotech organizations; includes high-volume agent tokens, access to Synthetic Evolution®, custom integrations, advanced security, and single sign-on (SSO).

Notable Customers and Partnerships

• LanzaTech: Uses TeselaGen as a foundational platform for automated biological design supporting carbon recycling technology, as noted by Dr. Michael Kopke, VP of Synthetic Biology.
• Twist Bioscience: CEO Emily Leproust highlights the integration between Twist and TeselaGen as delivering speed, lower cost, and a significantly reduced cost per data point.
• ABPDU (Advanced Biofuels and Bioproducts Process Development Unit): Collaborating with TeselaGen to streamline information flow throughout fermentation processing.
• Protein Evolution: Leverages TeselaGen's automation and software capabilities to reduce cost barriers and expand the scope of platform-level protein engineering.

TeselaGen is purpose-built for modern biological R&D teams seeking to move from idea to experiment faster, with AI agents that integrate directly into existing laboratory infrastructure and scale from individual researchers to enterprise-level pharmaceutical operations.