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Company description

Potato is a life sciences software platform designed to accelerate scientific execution for researchers across academia and industry. By combining an AI co-scientist named Tater, an extensive literature database, and a suite of scientific tools, Potato enables life science researchers to creatively design and execute experiments from end to end — from initial idea through data analysis and reporting.

Potato serves a broad range of R&D professionals, including wet lab biologists developing new workflows outside their area of expertise, computational biologists comparing tools and parameters in parallel, data scientists and bioinformaticians designing and adopting new analytical methods, and automation engineers looking to quickly translate protocols into robotic scripts. The platform is trusted by thousands of scientists and is available through free and paid plans.

Core Workflow with Tater, the AI Co-Scientist

• Give Tater a project: Users can upload a paper, dataset, or describe a need in natural language — such as analyzing data, troubleshooting an experiment, engineering a protein, or designing an assay.
• Plan and refine: Drawing on an extensive literature database, Tater translates scientific intent into a reproducible workflow grounded in the latest knowledge from the relevant field. Users can review and refine details throughout the process.
• Execute experiments: Tater leverages computational tools, delivers protocols, and can translate them into robot-ready scripts for automated systems. It is also capable of analyzing raw results and generating figures.
• Review results and iterate: Each run produces a final report outlining every step Tater took. From there, users can explore variations, alternative next steps, or new strategies in parallel.

Key Capabilities

• Literature search and synthesis: Potato enables researchers to search and synthesize scientific literature to inform experimental design and decision-making.
• Experimental design acceleration: The platform helps streamline experimental design, workflow execution, and data analysis, allowing scientists to focus on discovery and innovation.
• Idea exploration: Potato quickly shapes early-stage ideas into executable plans, branching into hundreds of possibilities to help researchers uncover new insights.
• Protocol generation: Potato produces highly accurate protocol drafts — one user reported saving 8–12 hours of manual work per protocol, with only 45 minutes needed for review and polishing.
• Automation integration: Protocols can be translated into robot-ready scripts compatible with automated laboratory systems.

Security and Data Privacy

• User data ownership: Users retain all rights to everything they upload, including papers, data, and prompts. These are not shared outside the user's private workspace. LLM-generated content is fully owned by paid account users, while free users have the right to use generated content internally.
• Secure by default: Potato is built from the ground up with modern security best practices. Uploaded information is only viewable by users within a controlled Workspace and can be deleted at any time.
• No training on user content: Potato explicitly prohibits using uploaded or generated content from paid accounts to train or improve its AI models, ensuring that what users share remains private.

Potato offers both free Open Access and premium paid plans, making it accessible to individual researchers as well as larger R&D teams seeking collaborative and advanced features.

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Software attributed to Potato AI

• PotatoView

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