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Agilent acquires artificial intelligence technology to enhance lab productivity

Agilent Technologies

Agilent will integrate the technology into its lab informatics platforms enabling customers to automate GC/MS data analysis

21 Feb 2022
Blake Forman
Content Creator

Industry news

Agilent Technologies has announced it has acquired advanced artificial intelligence (AI) technology developed by Virtual Control, an AI and machine learning software developer that creates innovative analysis solutions in lab testing. Agilent will integrate the software, known as ACIES, into its industry-leading gas chromatography and mass spectrometry (GS/MS) platforms to improve the productivity, efficiency, and accuracy of high-throughput labs the company serves around the world.

With the acquisition, Agilent obtained the software and other assets associated with ACIES. As part of the transaction, core members of the ACIES team also became Agilent employees.

ACIES automates the labor-intensive task of gas chromatography/mass spectrometry data analysis improving efficiency in the laboratory workflow, from sampling to reporting. Agilent will integrate the technology into its MassHunter software package for LC/MS and GC/MS instruments.

“Our acquisition of this advanced technology is just one more example of Agilent’s focus on delivering the insights and innovation our customers can use to provide industry-leading solutions,” said Jacob Thaysen, president, Agilent Life Sciences and Applied Markets Group. “We’re extremely pleased to be adding these additional capabilities to our product lineup.”

A range of industries and applications will benefit from Agilent’s acquisition of the technology, including food testing and agriculture, environmental, and applied materials, with broad potential to expand to other large markets.

The acquisition is Agilent’s latest investment in digital technology to improve lab productivity. It builds on the company’s existing investments and innovations to advance the analytical lab and transform its capabilities with new technology, better integration of instruments and data, and more efficient lab workflow.

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