Tesela AI

Tesela AI is an agentic co-scientist platform for biological R&D, developed by TeselaGen. It deploys specialized autonomous AI agents that design DNA libraries, generate assembly protocols, optimize biomolecules, and analyze experimental data — executing real scientific algorithms rather than simply generating text. Tesela AI is built for research scientists, computational biologists, and lab automation teams working across the full Design-Build-Test-Discover (DBTL) cycle.

The platform is accessible natively within the TeselaGen Platform (including Community Edition), through direct ELN/LIMS integrations, via a Python SDK and REST API, and — coming soon — through Model Context Protocol (MCP) connections to AI hosts such as Claude or ChatGPT. A free tier offering 100 agent runs per month is available with no credit card required.

Library Designer Agent

• Accepts natural language descriptions or existing sequence registry inputs to create combinatorial DNA libraries
• Supports multiple assembly strategies including Golden Gate, Gibson, MoClo, USER, and PCR
• Automatically reuses parts from your existing registry and identifies parts from public databases
• Generates simple or combinatorial library designs with part cost estimates, capable of producing up to 384-variant libraries in minutes

Library Construction Optimizer Agent

• Automatically generates complete, assembly-ready protocols including primer design with Tm calculation and validation
• Produces automatic plate map generation and PCR assignment
• Performs zone gradient thermocycler optimization and optimization of assembly protocol parameters
• Optimizes assembly overhangs and supports codon adaptation for protein expression
• Generates worklists compatible with lab automation equipment, eliminating manual protocol writing

Experiment Optimizer Agent

• Powered by TeselaGen's patented Synthetic Evolution® machine learning engine, delivering 10x faster convergence than random screening approaches
• Analyzes experimental results and predicts top-performing variants for yield, titer, or binding affinity
• Employs generative models to propose novel sequence leads
• Provides automated DBTL cycle recommendations to close experimental loops faster
• Supports custom ML model training on proprietary experimental data

Data Analyst Agent

• Ingests multi-format data from plate readers, sequencers, and analytical instruments (CSV, Excel, instrument-native formats)
• Performs automated statistical analysis and visualization of experimental results
• Carries out sequence alignment and validation for both Sanger and NGS data
• Recommends next experimental steps based on defined objectives, turning raw data into actionable insights

Workflow Designer Agent (Coming Soon)

• Orchestrates end-to-end experimental workflows by composing protocol steps from Library Designer and Library Construction Optimizer outputs
• Generates high-throughput worklists for liquid handlers including Tecan, Hamilton, Echo, and Biomek
• Supports multi-plate experiment orchestration and tracking
• Integrates with LIMS and lab automation systems
• Provides real-time execution monitoring and error handling

Integration and Connectivity Options

• TeselaGen Platform (Native): AI agents work directly with sequences, designs, and experimental data within the platform, including the Community Edition
• ELN/LIMS Integration: Scientists can invoke AI agents without leaving their electronic notebook; agents read sequences, registry data, and assay results, then write designs and protocols back automatically
• Python SDK and REST API: Full programmatic access to all agent capabilities for computational biologists working in code
• Model Context Protocol (MCP, Coming Soon): Connects Tesela AI to Claude, ChatGPT, or any MCP-compatible AI host, allowing scientists to access library design, protocol generation, and optimization through their preferred AI interface

Key Differentiators

• Agents execute real scientific algorithms — including primer design, assembly optimization, sequence validation, buildability checks, and data parsing — not LLM wrappers
• Proprietary Synthetic Evolution® engine is backed by multiple issued US patents on AI-accelerated biotech
• Platform-agnostic architecture works with many ELNs and LIMS, or standalone, without requiring tool switching
• Covers the full integrated DBTL loop so that each experiment automatically informs the next

Tesela AI is designed to be platform-agnostic and fits into existing laboratory infrastructure through flexible API, SDK, and MCP connectivity. It is suitable for teams seeking to accelerate biological R&D without replacing their current ELN, LIMS, or automation stack.