Main challenge

Turning complex scientific data into an AI-powered discovery engine.

  • Complex scientific data

    Structuring experimental and AFM data so AI systems can work with it.

  • AI grounded in science

    Supporting AI reasoning without losing the underlying experimental context.

  • From insight to action

    Connecting analysis and hypothesis generation to practical research workflows.

  • One evolving platform

    Bringing AI, data science, and scientific software together as the research platform continues to evolve.

Project approach

From workflow discovery to platform delivery.

Building around the science, not around the AI.

The collaboration focuses on connecting AI, data science, and scientific software around In Physico's research environment, with the platform evolving alongside the scientific work.

Collaboration scope

AI infrastructure supporting the evolution of the In Physico Discovery Engine.

CodePhusion works across AI engineering, data science, and scientific software as part of the ongoing development of In Physico's research platform.

  • AI Engineering

    AI systems and workflows designed for scientific research environments.

  • Data Science

    Data-driven approaches for extracting insight from complex scientific information.

  • Scientific Software

    Software capabilities connecting research workflows, data, and computational tools.

Ongoing collaboration

An evolving collaboration around AI-powered scientific discovery.

The Discovery Engine continues to evolve alongside In Physico's research, with CodePhusion supporting the AI and software infrastructure behind the platform.