Legal Visualization and AI
Graph visualization, graph analytics, and large language models (LLMs) are powerful tools that significantly enhance the process of investigating legal clauses in documents and contracts. Graph visualization enables the representation of complex relationships between clauses, terms, and entities in a legal document as a network of interconnected nodes and edges. This visual representation allows legal professionals to quickly identify patterns, connections, and potential issues within a contract, such as overlapping clauses or conflicting obligations. By visualizing these relationships, it’s easier to navigate and comprehend the structure of lengthy and intricate legal documents.
Thanks to LLMs like GiNER and frameworks like Relik it’s nowadays possible to ingest large amounts of documents and create a knowledge graph out of it. There are also services like LlamaPArse which can return high-quality JSON from any given PDF or image. In the old days one had to use computer vision and all sorts of tricks (removal of smudges and folds anyone?) together with classic NLP to do this. This is one domain where I can confess that AI has taken over the job of developers. The amount of time and money you save via the AI road is astounding.
In most cases yFiles is the best choice to render complex structures because of the advanced/flexible layout algorithms but we also had a few projects based on GoJS. There is no question that yFiles gives qualitatively better results but some startups prefer to start with GoJS due to budgetary constraints.
Graph analytics further supports the legal investigation by applying advanced algorithms to the graph structure, uncovering hidden patterns, trends, and anomalies that may not be immediately apparent through manual review. For example, graph analytics can be used to identify frequently occurring clauses across a set of contracts, assess the centrality of certain terms, or detect subgraphs that represent standard contract structures. By analyzing the properties and behaviors of these graphs, legal teams can gain insights into common practices, potential risks, or even suggest optimizations to contract structures, thereby making the review process more efficient and thorough.
Beyond visual analysis and graph analytics, LLMs can be trained on vast amounts of legal text, enabling them to comprehend and generate human-like text based on the context provided. This capability is invaluable for interpreting complex legal language, identifying inconsistencies, or suggesting alternative wording. Additionally, LLMs can automate the extraction of relevant clauses or summarize lengthy contracts, reducing the time required for initial document reviews. When combined with graph visualization and analytics, LLMs provide a robust toolkit for legal professionals, enabling them to navigate, analyze, and understand legal documents with unprecedented depth and precision.
Over the years, we have had the privilege of assisting a wide range of legal firms, from small boutique practices to large, multinational law firms. Our work with these organizations has provided us with deep insights into the evolving challenges and opportunities within the legal sector. The integration of AI technologies has brought about a transformative shift in this domain, revolutionizing how legal work is conducted, from contract analysis to case management.
AI has fundamentally changed the legal industry by automating routine tasks, enhancing decision-making processes, and improving the accuracy and efficiency of legal research. For small firms, AI has leveled the playing field, allowing them to compete with larger firms by providing access to advanced tools that streamline their operations and reduce costs. Larger firms, on the other hand, have leveraged AI to manage vast amounts of data, enabling them to handle complex cases and voluminous contracts with greater speed and precision.
The impact of AI on the legal sector is profound and ongoing. As AI continues to advance, it’s reshaping not only the way legal services are delivered but also the very nature of legal work itself. From predictive analytics that anticipate case outcomes to NLP processing that enhances contract drafting and review, AI is enabling legal professionals to focus more on strategic thinking and client relationships, while routine tasks are handled more efficiently and accurately than ever before.