Automata provides an integrated lab automation platform that combines modular LINQ hardware with a no‑code Workflow Canvas and a Python SDK for designing and executing genomics, cell biology, and screening protocols. The cloud‑native system offers real‑time run monitoring, version‑controlled workflow management, and REST APIs for LIMS and AI pipeline integration, enabling high‑throughput, reproducible experiments.
Funding
$40M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
+1Founders
Product
Problem
Laboratory teams often rely on fragmented equipment and manual protocols, which limit sample throughput, increase error rates, and make it difficult to capture reproducible data for downstream AI analysis. Scaling experiments across multiple assay types (genomics, cell biology, screening) typically requires custom integration work and extensive operator training.
Solution
Automata delivers a fully integrated lab automation platform that combines modular LINQ hardware with a unified software stack. The node‑based Workflow Canvas enables users of any skill level to design complex protocols without writing code, while the Python SDK provides programmatic control for custom steps and simulation on digital workcells. Real‑time Run Manager tracks execution, issues alerts, and supports remote monitoring, allowing teams to manage experiments from any browser. A cloud‑native orchestration layer permits concurrent workflow execution and versioned engine/driver selection, with GitHub synchronization to enforce deep version control. Open REST APIs let external LIMS, data lakes, and AI pipelines ingest and transform in‑process data, turning the lab into a continuous data powerhouse.
Target Audience
The platform targets automation engineers, R&D scientists, and assay development teams in biotech, pharmaceutical, and academic core facilities that need high‑throughput, reproducible wet‑lab workflows and integrated data pipelines.
Features
- Node‑based, no‑code Workflow Canvas for drag‑and‑drop protocol assembly across genomics, cell biology, and screening assays
- Python SDK offering full lifecycle control, simulation, and custom code steps within the workflow engine
- Run Manager dashboard with real‑time status, automated alerts, remote start/stop, and secure browser access
- Cloud platform that supports concurrent workflow execution, tag‑based sample tracking, and scalable compute resources
- Deep version control linking specific hardware driver and engine releases to individual workflows, with GitHub sync for reproducibility
- RESTful API layer for seamless integration with LIMS, data warehouses, and machine‑learning pipelines
- Modular LINQ hardware suite (liquid handling, plate readers, incubators) designed for plug‑and‑play expansion and easy maintenance