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Protocol Engine Data Fabric AI Agent
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AI Agent

Analysis code, on demand, from a plain-language prompt.

Every research team has analyses that don't fit an off-the-shelf tool — fold-change calculations, dose-response curve fits, custom normalization. Describe what you need. The AI Agent writes real Python, runs it in an isolated environment, and returns the result with the full code attached.

Capabilities

The custom analysis tool, without the bioinformatician wait time.

  • On-demand analysis tool generation

    Describe your analysis in natural language — "calculate fold-change for conditions A vs B, normalize to housekeeping control, flag wells outside 2 SD." The agent writes real, executable Python and runs it immediately against your experiment data.

  • Runs in sandboxed environment

    All generated code executes in an isolated container. Your instrument data and assay results stay within your workspace. The agent reads what you point it at and nothing else.

  • Full audit trail of generated code

    Every generated tool is stored with the prompt that created it, the input dataset, and the output produced. Any analysis can be re-run identically — or forked with a modified prompt — without reconstructing what was done.

  • Team-level tool library

    Tools the AI generates are added to your team library. The next researcher who needs a similar analysis starts from existing, tested code.

AI agent concept: symbolic representation of an intelligent agent examining scientific data and producing protocol steps
cypher agent — code generation
you > Calculate fold-change for conditions A vs B from plate_reader_output.csv def calculate_fold_change( data_path: str, condition_a: str = "A", condition_b: str = "B" ) -> pd.DataFrame: # reads CSV, groups by condition, returns fold-change

Custom analysis tools, without the custom development timeline.

Request early access and we'll show you the AI Agent running against a real assay workflow.

Request Early Access