As part of a large reorganization project, a multinational client retained Blakes to assist it in assigning licensing agreements to a single corporate entity.
Blakes lawyers combined their expertise in reviewing contracts with the power of machine learning to facilitate the assignments.
Given the success and efficiency of this work, the client expanded the project, using the same solution to complete a broader review of key legal and business terms in its licensing agreements.
Our client had more than 700 global licensing agreements to assign to a single corporate entity. Keeping the work in-house would have overwhelmed its legal team’s capacity. Further, a strictly manual review would have taken too long and incurred unnecessary costs.
The challenge was to save our client time and limit costs while ensuring a thorough, accurate review.
We recognized that we could best meet our client’s needs by combining the strengths of our people and technology.
Blakes inSource provided the people power. Our in-house alternative legal service provider, inSource is staffed with lawyers who have expertise in contract review.
The technological tools came from Blakes Assure, an innovative solution that uses machine learning to analyze documents. This technology allowed our team to quickly identify and compare provisions of interest in our client’s agreements.
Blakes facilitated the assignment of all the client’s licensing agreements on time and on budget. Our process was much more efficient than a strictly manual review — and just as accurate.
Given the success of the original mandate, the client expanded the project and had Blakes use the same solution to complete a broader review of its licensing agreements for key legal and business terms. This work improved our client’s understanding of those terms, allowing it to work toward standardizing them.
In total, inSource efficiently reviewed approximately 750 agreements for 25 different legal and business provision types. Our team provided detailed summaries of each agreement and thorough analyses of trends and practices across different provision types.
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