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Family Law Partners have always considered technology to have a pivotal role in the future delivery of family law services, and Director Alan Larkin first approached the university seeking to integrate artificial intelligence into everyday legal practice in 2017. 

Through their development and support of Siaro, their , and their exploration of predictive data analytics, Family Law Partners had already understood and felt first-hand the potential technology had to positively impact on their business, their clients, and the sector as a whole. 

By partnering with university experts in rule-based systems, and applying artificial intelligence methods, the partnership developed an innovative system which automated some previously manual processes, making use of ‘rules’ in order to develop an innovative triage style family law system. 

There are very limited examples of the successful application of artificially intelligent systems approaches to Law, so this KTP offered a highly innovative opportunity for collaboration. 

The academic team, Dr John Kingston and Dr Andrew Montgomery from 欧美性爱片’s School of Architecture, Technology and Engineering had particularly relevant knowledge and experience in Information Systems, Artificial Intelligence (AI), Business Computing, Law and legal practice – an unusual combination as typically, the Legal sector is not known for its innovation in IT.  KTP funding enabled Samashwin Paul, to be appointed as KRP Associate, Knowledge Systems Developer to deliver the project. 

Family Law Partners had already developed a conditional logic system themselves, however they lacked deeper computing expertise to turn their innovative ideas into a reality. Using expertise in artificial intelligence, rule-based systems and software development the team addressed various ‘pain points’ in family law legal process – some of the more onerous or demanding steps in the process and developed a system to deliver efficiency and costs savings to clients.

• This innovative partnership embedded knowledge engineering expertise to develop a rules-based decision support system to underpin a novel model of family law provision. 
• The system also streamlined some arduous manual processes and provided alternatives to the court system, which had previously caused bottlenecks in the workload. These system and process efficiencies also resulted in a reduction in the expense of some legal processes, such as divorce or separation. 
• Artificial Intelligence methods were applied to enhance the assessment of incoming cases, improving outcomes.  
• Rule-based systems development and implementation - staff where specify trained to implement methods within a rule-based AI system. 
• Software and a web-based platform were also developed as part of the project.