Legal.

Overview

Legal

Our Services

  • Building custom AI-supported workflows and integrated AI platforms into existing systems.
    • Secure, confidential, locally hosted LLMs that are finetuned for the needs of the firm, including generating draft research and issue memos, case law analyses, summary of key documents, and checklists.
    • Assisted authoring and editing of documents, which allow for faster, more comprehensive and quality drafting of legal documents that draw.
  • Consultation on choosing the right frameworks, technology stacks and LLMs suited for your firm, hastening speed, improving performance, and reducing costs.
    • Facilitating knowledge sharing and database searches that make the firm’s internal repository of documents and analyzes easier to access.
  • Hands-on workshops (1-day/3-day bootcamps to upskill the workforce on effective use of AI and latest tools) and feedback-loop sessions.
    • Ensuring that custom LLMs respond to and build upon the strengths of the Firm’s Partners and Senior Associates, becoming a repository that ensures consistent quality across the Firm’s work products.

Our Platform performs the following key functions:

  • Summarizes lengthy legal documents such as contracts, court transcripts, or deposition transcripts, saving lawyers and paralegals a significant amount of time and effort.
  • Seamlessly conduct research by analyzing large volumes of legal documents and providing insights into case law and legal precedent. By simply inputting the relevant query to our system, quickly identify relevant cases and provide summaries and analysis of those cases.
  • Analyze documents such as pleadings, briefs, and court transcripts for identifying potential weaknesses or strengths in arguments made by opposing parties.
  • Predict the outcome of legal cases by analyzing past cases with similar fact patterns and outcomes. Make more informed decisions about how to proceed with a case.
  • Assisted Authoring feature to harness the knowledge gained from our seamless processing and understanding of uploaded documents, and effortlessly create new, meticulously crafted documents in a fraction of the time it would take manually.
  • Documenting notes of client meetings and creating a client-specific database that contributes to the Firm’s institutional knowledge of businesses, sectors, industries, and trends

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AI Applications

One AI application for businesses facing the choice between open-source and proprietary models to deploy generative AI is natural language processing (NLP) for customer service or support chatbots. Businesses can utilize generative AI models to develop chatbots that can understand and respond to customer queries in a more human-like manner. The choice between open-source and proprietary models can impact the accuracy, scalability, and customization capabilities of the NLP models deployed in these chatbots.

Additionally, another AI application is the development of recommendation systems. Generative AI models can be used to create personalized recommendations for products or content based on user behavior and preferences. The choice between open-source and proprietary models can affect the quality of the recommendations, as well as the ability to tailor the recommendation system to specific business needs.

Furthermore, businesses can leverage generative AI for content generation, such as automated text summarization, language translation, and creative writing. The choice between open-source and proprietary models can influence the linguistic fluency, coherence, and originality of the generated content.

In each of these applications, the decision between open-source and proprietary models for generative AI deployment can significantly impact the performance, interpretability, and ethical considerations of the AI systems utilized by businesses.