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Automating a lab is hard work. Robots, software, instruments, data flows – everything has to move in sync, or scientists end up spending more time wrestling with tools than running experiments. That is the gap Automata wants to close as it doubles down on building AI‑ready labs for the life sciences world.
The London‑based lab automation company has just raised a fresh $45 million Series C round to push that vision forward. The new funding is led by Dimension, with participation from Danaher Ventures, Tru Arrow Partners, Octopus Ventures, Entrepreneurs First, and other existing backers. Alongside the capital, Automata has also secured a strategic investment partnership with Danaher Corporation, one of the biggest names in life sciences instruments and diagnostics.
Automata is not new to the world of automation and robotics. Co‑founders Mostafa ElSayed and Suryansh Chandra originally started the company after seeing how automation could move beyond architecture and into other complex environments. Over time, they shifted focus from affordable robotic arms to fully integrated lab automation, with ElSayed now leading the company as CEO. Today, Automata’s mission is simple to explain but hard to execute: turn traditional wet labs into programmable, autonomous systems built for the age of AI.
To do that, Automata is building what it calls a reference architecture for autonomous wet labs. Instead of isolated robots running single tasks, its platform connects modular robotics, orchestration software, and a unified data layer. The end result is a lab that looks and behaves more like an automated factory line for experiments – repeatable, trackable, and ready to plug into computational tools. For pharma and biotech teams trying to link AI models with real‑world experiments, this kind of setup is becoming a must‑have rather than a nice‑to‑have.
The timing of the Series C says a lot about where the industry is heading. AI has transformed how we model biology and design new molecules, but the physical side of experimentation often lags behind. Many labs still rely on manual workflows, siloed instruments, and disconnected software that make it hard to scale or standardize. Automata is positioning itself as the bridge, offering “AI‑ready” labs that can run complex workflows with minimal human intervention while keeping data clean and structured end‑to‑end.
The numbers behind the business are also starting to look serious. Automata is already working with five major pharmaceutical companies and has been involved in some of the largest lab automation programs in the industry. Much of this growth comes from repeat deployments, as teams roll out the platform across multiple sites once the first lab proves its value. When a lab can run more experiments in less time, with better data quality and fewer errors, it becomes easier to justify expanding that model across an entire network.
Danaher’s involvement takes the story a step further. Through Danaher Ventures’ participation in the round, the two companies are setting up a strategic partnership that links Automata’s automation stack with Danaher’s portfolio of instruments, reagents, and software. Technologies from Danaher businesses such as Molecular Devices and Beckman Coulter Life Sciences are expected to integrate Automata’s software, enabling more complete “lab‑in‑a‑box” style solutions. For labs under pressure to speed up discovery while holding down costs, this kind of tight integration can remove a lot of custom engineering and one‑off scripting.
There is also a cultural shift happening in how scientists think about automation. In older setups, researchers often had to “program the robot” directly, learning vendor‑specific interfaces or relying on specialists. Automata’s approach flips that around by letting scientists focus on programming the experiment instead. The platform takes care of translating those workflows into coordinated steps across robots and instruments. That not only makes automation more accessible, it also lowers the barrier for teams that might not have deep coding expertise in‑house.
With the new capital, Automata plans to scale both its technology and its reach. The Series C funding will accelerate platform development, from software orchestration and data infrastructure to support for new instrument types and workflows. It will also help the company keep up with rising demand from pharma and biotech customers that want to redesign their labs around higher throughput, better reproducibility, and tighter links to AI pipelines.
For futureTEKnow readers who track how automation is reshaping industries, Automata is a good example of a company sitting right at the crossroads of robotics, software, and life sciences. Its latest round is more than just another funding headline. It signals growing conviction that the next generation of drug discovery and biological research will depend on labs that can operate like programmable platforms, not manual workshops. If Automata can keep executing on that vision, the humble wet lab might soon feel as programmable as the code that drives it.

Editorial Team
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