Australasia News
Maddocks has adopted Luminance’s machine learning technology to streamline the due diligence processes at the Australian firm. The firm, which has long been committed to improving client service through innovation, selected Luminance due to its ability to significantly reduce the amount of time spent on a due diligence review compared to typical manual methods.
In particular, Maddocks valued the platform’s unsupervised machine learning capabilities, which identified new clauses, similarities and differences within contracts in the data room from day one of the pilot.
“We have been looking for an AI tool to help assist with the streamlining of our due diligence processes and Luminance provided a good solution for us,” added Ron Smooker, Partner at Maddocks. “The platform provides our lawyers with an instant insight into the data room, allowing them to structure our review and deliver considerable time savings and efficiency gains compared to a manual review alone. We’re looking forward to exploring the opportunities Luminance can deliver in our business and pass these benefits on to our clients.”
“We’re excited for Luminance to have been selected by Maddocks to support its lawyers on corporate transactions,” said Emily Foges, CEO of Luminance. “The firm understands the importance of innovation in the legal sector and their adoption of Luminance will allow the firm to continue providing the highest-quality legal services to its clients.”
Luminance applies the latest advances in machine learning technology developed by mathematicians from Cambridge University. The platform reads and understands legal documents in a similar way to humans, coping with volumes and working at speeds that no human can match. The technology instantly sorts and classifies documents while highlighting possible anomalies for lawyers’ review.
Luminance has over 75 customers in 23 countries across five continents since launching in September 2016. The company was recently awarded ‘Enterprise Startup of the Year’ at The Techies 2018.
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