The future of scientific discovery starts with AI-ready labs

London-based Automata Technologies is developing lab automation infrastructure that combines robotics and software with existing scientific instruments to make life sciences labs AI-ready, according to a Business Reporter article. Automata argues that automation creates the most value as a connected system rather than a collection of isolated automated steps, built on three principles: full integration across instruments, workflows and data regardless of vendor; ease of use for both scientists and automation engineers; and AI readiness. The company says connected infrastructure can increase throughput and walkaway time, letting labs test more ideas without equivalent increases in headcount or facilities.

The future of scientific discovery starts with AI-ready labs THE ARTICLES ON THESE PAGES ARE PRODUCED BY BUSINESS REPORTER, WHICH TAKES SOLE RESPONSIBILITY FOR THE CONTENTS - Bookmark Become an Independent member to bookmark this article Want to bookmark your favourite articles and stories to read or reference later? Start your Independent Membership today. Join today https://www.independent.co.uk/subscribe?regSourceMethod=Bookmarks Already a member? Log in Behind every new cancer drug, diagnostic test or vaccine is a laboratory doing work that rarely makes the headlines: thousands of experiments, run and rerun, refined a little each time until something works. For decades, much of that work has been done by hand: one scientist, one pipette, one repetition at a time. A scientist may spend hours preparing and moving samples before recording the results. These processes don’t just require extraordinary precision. They take time. Time that isn’t spent asking questions, interpreting findings and deciding what to try next. This is starting to change, and one of the British companies leading the shift is London-based Automata Technologies. https://www.automata.tech/ It develops lab automation infrastructure for life sciences labs, combining robotics and software with the scientific instruments they already use. That connected infrastructure is becoming increasingly important as life sciences organisations prepare for wider use of AI in the lab. In practice, co-ordinating instruments, workflows and data can increase throughput and create more walkaway time, allowing experiments to run more consistently and, in some cases, without constant supervision. Labs can therefore test more ideas and identify promising results sooner without equivalent increases in headcount or facilities, which can shorten the path towards new medicines and expand access to diagnostic testing. For many life sciences organisations, the question is no longer whether to automate their labs but how to do it effectively. Pharmaceutical, biotechnology and diagnostics organisations are under pressure to move faster, produce more reliable data and achieve more with existing people and resources. AI has raised the stakes further. It can analyse data and help researchers identify what to test next, but realising its full value will depend on labs being able to carry out those experiments and return reliable, usable results. However, much of today’s lab automation is not equipped to do that. Equipment can automate individual stages but may not communicate with what comes before or after, leaving scientists to move samples and information between them. Vendor lock-in can compound the problem by tying labs to closed systems that are difficult to adapt as scientific and AI requirements evolve. Automata Technologies has built its approach around closing those gaps. Rather than adding another isolated tool, Automata starts from a simple observation: automation creates the most value when it works as a connected system https://www.automata.tech/blog/autonomous-labs-infrastructure-point-solutions , not as a collection of automated steps. That thinking shapes Automata’s work across commercial and academic life sciences, serving scientists running experiments, as well as the R&D and operations leaders responsible for how the wider lab performs and scales. That approach is built on three principles. The first is full integration. Instruments, workflows and data need to connect end-to-end, regardless of vendor. This allows labs to adapt their equipment and processes over time without being tied to a single manufacturer’s ecosystem. The second is ease of use. Scientists and automation engineers need to be able to work within the same system without unnecessary friction, which means tools need enough depth for specialists while staying accessible to everyone else touching the workflow. The third is AI readiness. For Automata, that does not mean simply labelling a product “AI-powered”. It means building the structured data and flexible architecture https://www.automata.tech/blog/unified-data-unlocks-ai-workflows that allow AI models to be applied meaningfully to lab operations. These three principles come together in Automata’s LINQ platform https://www.automata.tech/linq , which combines modular lab hardware, orchestration software that co-ordinates instruments and workflows, and an open data architecture into a single system. The payoff is not automation for its own sake. It is a shift towards lab operations that are more reliable, more scalable and increasingly autonomous over time. As AI reshapes the life sciences sector, Automata’s position is that the real differentiator is not any single instrument or feature, but whether the lab can operate as a connected whole: integrated, usable and ready for future applications of AI. Learn more about Automata’s approach to connected lab automation https://www.automata.tech/linq .