Luminance’s Legal Inference Transformation Engine (LITE) is the core intelligence that powers Luminance’s ability to rapidly analyse and form an understanding of documents. LITE combines a number of disciplines within the field of machine learning, including inference, deep learning, natural language processing and pattern recognition. Further, Luminance is the only system that combines both supervised and unsupervised machine learning, ensuring lawyers are provided with the most rigorous document analysis possible.
Luminance is primarily deployed in the cloud and requires no pre-training or configuration: customers typically begin their review within hours of installation.
Unsupervised machine learning does not require any a priori knowledge of labels or tags in order to solve a problem. Instead, the machine is exposed to vast datasets and by analysing these in their entirety, the underlying patterns of the data are revealed. The system quickly builds up a pattern of what is normal – and thus what is abnormal.
Only unsupervised machine learning, which does not rely on understanding documents in relation to given labels, surfaces the ‘unknown unknowns’ – issues that the reviewers did not know existed and thus never searched for them or labelled them, but that nonetheless present as a significant anomaly. This is critical in due diligence as all risk is surfaced immediately within the review and negotiating positions can be strengthened from the outset. Similarly in eDiscovery, unsupervised machine learning can help litigators quickly find the smoking gun amongst mountains of irrelevant material.
Within supervised machine learning, the system is exposed to examples of data that are described and defined. The system forms an understanding of what makes up each classification, and can apply these to new datasets that it sees.
In fact, Luminance’s technology takes supervised machine learning a step further, as it continues to learn from the ways that lawyers interact with the platform, too. By observing the actions of legal professionals, Luminance can form an understanding of what lawyers are looking for in their documents, meaning that Luminance actually becomes more intelligent and bespoke for each lawyer the more that they use the platform.
Older approaches, such as rules-based systems, rely on programmers or consultants pre-defining concepts and search terms which they consider to be of relevance. Unsurprisingly, manual systems such as these take months or even years to configure, require advanced training for lawyers to use and are highly costly to build. The system becomes out of date quickly as updates to regulation or legal frameworks come in, and thus this results in further bespoke programming at considerable expense. But crucially, such systems lack the flexibility to deal with variations in terms or to recognise anomalies within the data.
Other systems apply machine learning in a rudimentary manner, or only apply only a subset of machine learning to the problem. Whilst supervised machine learning is integral, unsupervised machine learning is also needed to tackle other parts of the problem. Indeed, supervised and unsupervised machine learning serve different purposes - they both have their place and when combined they supercharge document review. In situations where it is critical to surface every single risk and anomaly, lawyers need to have the power of each system within their arsenal, and Luminance is the only technology to employ both.
Luminance is primarily deployed in the cloud, allowing lawyers instant access whether they are in the office, at client sites or working remotely. With no time wasted on pre-training, rule creation or machine configuration, Luminance users are typically preparing to start their first review after just 30 minutes. Luminance will straight away surface results to lawyers, providing real value from day one.
With data security of critical importance to any organisation, Luminance’s robust security protocols ensure no documentation risks being exposed. Luminance has the highest levels of security built in, and the company is overseen by a world-leading security advisory board comprising experts from cybersecurity technology to nation state-level security.
Adapting to regulatory changes when using legacy systems often means expensive and time-consuming manual updates are required, or entire sets of documentation need to be re-examined in light of a change to legal frameworks. With Luminance, machine learning will automatically surface documentation that is no longer consistent with regulation and won’t need to undergo costly maintenance following changes in law.
Luminance is routinely used by boutique firms of less than 10 lawyers. On the other end of the spectrum, Luminance is in use by one-fifth of the Global 100 Law Firms and all of the Big Four accountancy firms. Luminance has been used on some of the world’s largest legal cases, handling tens of millions of documents without challenge. No matter the size of firm or matter, Luminance can scale to fit the requirements.
Over the course of M&A due diligence review, Luminance’s powerful tools have consistently led to over 75% time savings compared to traditional methods. From document analysis to task allocation and monitoring, Luminance streamlines the review process, leaving more time for higher-level legal analysis. For example, Bird & Bird were able to review 79 documents per hour prior to using Luminance. When assisted by Luminance, this jumped to 3600 per hour.
By combining supervised and supervised machine learning, Luminance is the most robust AI platform for lawyers. From a missing page or clause to a minor difference in wording, Luminance provides legal teams with a comprehensive understanding of a project, giving lawyers confidence that no risk has been missed and putting them in the best possible position for negotiations or litigation.
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