Pharmaceutical & Biotech
Lab automation, sample handling, and learning-ready data for drug discovery and diagnostics.
Industry Context
Pharmaceutical and biotech labs face intense pressure for reproducibility, throughput, and compliance. Manual pipetting, sample transfer, and plate handling introduce variability and limit scale. Learning-based robotics can automate these workflows while adapting to new assays and formats — but only with high-quality, task-specific data.
What We Offer
- Data Collection — We collect demonstrations for pipetting, sample handling, plate transfer, and tube management. Data is formatted for imitation learning (e.g., OpenVLA, Octo fine-tuning) with synchronized vision and actions.
- OpenArm & Lab Platforms — Modular arms and lab-compatible hardware for integration with existing instruments. Data-centric design for continuous improvement.
- Fearless Data Platform — Upload failure logs from automated runs; get automatic replay, benchmarking, and policy A/B testing. Close the loop between deployment and improvement.
- RL Environment — Real-world RL environments for optimizing sample workflows, scheduling, and error recovery without disrupting production.
Value We Deliver
- Faster time-to-automation — Skip months of in-house data collection. We deliver learning-ready datasets for your specific assays.
- Reproducibility — Consistent, logged data. Traceability for compliance (e.g., 21 CFR Part 11) when integrated with your systems.
- Flexibility — Learning-based systems adapt to new plate formats, reagents, and protocols with minimal reprogramming.
- Reduced risk — Robots handle hazardous or sterile samples; humans focus on design and interpretation.
Example Use Cases
- High-throughput screening: plate handling, liquid transfer, reader integration
- Cell culture: flask handling, media exchange, passaging
- Sample prep for sequencing and diagnostics
- QC and inspection: visual and tactile quality checks