Startups doing autonomous scientific experimentation (self-driving labs)

1. Arctoris — Operates a robotic, remotely accessible drug-discovery laboratory that executes and analyzes experiments with software-controlled workflows; fits as an early-stage company built explicitly around autonomous, data-generating wet-lab experimentation, with venture backing and pharmaceutical partnerships.
2. Atinary Technologies — Provides AI-driven experiment-design and optimization software that connects to laboratory instruments to run closed-loop materials and chemistry experiments; fits as an early European startup focused directly on self-driving laboratory workflows rather than only predictive modeling.
3. Kebotix — Combines machine learning, robotics, and automated synthesis/testing to discover advanced materials; fits through its “autonomous materials discovery” model and its history of government funding, research collaborations, and commercial materials programs.
4. Chemify — Develops software and automated chemistry infrastructure intended to design and synthesize molecules with minimal human intervention; fits as a relatively young, well-funded company targeting autonomous chemical discovery and synthesis.
5. Adaptyv Bio — Uses automated microfluidic experimentation, high-throughput protein engineering, and machine learning to optimize biological molecules; fits as an early company whose core loop is AI-guided design, robotic testing, and iterative biological learning.
6. Aether Biomachines — Builds robotic and computational systems for automating biological experimentation, including cell and protein engineering workflows; fits as an early-stage “lab-in-a-box” style company aimed at making experimental biology more autonomous.
7. LabGenius — Runs automated protein-engineering campaigns in which machine learning proposes antibody variants and robotic systems build and test them; fits as a proven example of a closed-loop self-driving biology platform, supported by substantial venture funding and pharma collaborations.
8. Strateos — Provides cloud laboratories with remotely programmable robotic equipment for chemistry and biology experiments; fits as enabling infrastructure for autonomous experimentation, with a substantial installed platform and usage by biotech, pharmaceutical, and academic customers.
9. Emerald Cloud Lab — Offers a fully automated, remotely operated laboratory in which software can specify, execute, and monitor complex experiments; fits as a commercial cloud-lab platform with real operational scale, even though it is more infrastructure-oriented than a single-domain discovery startup.
10. Synthace — Provides software for programmatically designing, orchestrating, and analyzing automated biology experiments across laboratory instruments; fits as the control and data layer for self-driving labs, with enterprise deployments and partnerships in industrial biology and biopharma.

White-space gaps noticed:

• Autonomous experimentation for real-world manufacturing conditions: Many platforms optimize molecules or materials at bench scale, but fewer close the loop across pilot-scale synthesis, process economics, impurity analysis, and manufacturability.
• Self-driving labs for complex, poorly standardized biology: Protein engineering is relatively automation-friendly; there is still room for robust autonomous systems handling primary cells, organoids, microbiomes, animal-derived samples, and other variable biological models.