Zeon Systems Launches Natural Language Lab Automation Platform
Y Combinator-backed Zeon Systems has launched a robotics platform that translates natural language instructions into automated laboratory procedures. Scientists can describe experiments in plain English, and the system programs robotic arms to execute the protocols.
The startup was founded by Brontë, who previously built electronic systems for electric aircraft and battery packs before transitioning to computational biology research at UCSF, UC Berkeley, and Erasmus Medical Center. Co-founder Tahir brings experience in machine learning for scientific applications, having worked in computational research at IIT and Yale along with roles in biotech and pharmaceutical companies across India and the United States.
Zeon's system combines AI-powered software with off-the-shelf robotic arms equipped with depth cameras. The platform interprets written protocols, identifies laboratory equipment using computer vision, and generates robotic code in real-time to adapt to specific lab environments.
Current pilot programs at UCSF and Stanford demonstrate the system running fluorescence screens for nanoparticles, automating multichannel pipetting for clinical assays, and handling biohazardous waste disposal during off-hours.
"We want to enable labs that run themselves," the founders stated in their launch announcement, envisioning autonomous research facilities operating in remote locations like Mars or ocean environments.
Traditional laboratory automation requires significant upfront investment and custom programming for specific use cases. Zeon positions its solution as accessible to everyday scientists without specialized robotics expertise.
The company sells a complete hardware and software package that labs can deploy without extensive facility modifications. The system uses standard robotics components rather than purpose-built laboratory equipment.
Laboratory automation represents a growing market as research institutions seek to improve efficiency and reproducibility while addressing staffing challenges. Manual processes in scientific research have remained largely unchanged despite advances in other industries.
Zeon's natural language approach differentiates it from existing automation vendors that typically require programming knowledge or predefined protocols. The system can adapt to variations in lab layouts and equipment configurations.
The startup is actively seeking pilot partners across academic and commercial research facilities. Early applications focus on routine procedures like sample preparation and screening assays that consume significant researcher time.
Funding details were not disclosed, though the company participated in Y Combinator's latest batch. Zeon plans to expand its engineering team and scale pilot deployments throughout 2025.
The laboratory robotics market has historically served high-volume production environments rather than flexible research settings. Zeon's approach targets the broader research community that has been underserved by existing automation solutions.