Personal AI for Law Firms

When your legal workload exceeds the hours in your day.

Utilize legal-specific infrastructure, data, and collaboration to empower impactful efficiencies, including:

24/7 Attention

The legal field demands constant access to vast amounts of case-related information and client communications, a requirement that is both critical and challenging to meet. Stay on top of repetitive communication that takes your focus away from what is driving your business forward.

Efficiency While Maintaining Control

Balance the need for quick decision-making with the necessity of thorough analysis and meticulous oversight to ensure accuracy and compliance with legal standards.

Get useful, reliable, accessible data in real time.

Utilize legal-specific infrastructure, data, and collaboration to empower impactful efficiencies, including:

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Defragment Data

The management and retrieval of information from fragmented systems and platforms often result in inefficiencies, making it difficult for lawyers to quickly access relevant case precedents, documents, and client data.

Reduce Non-Billable Hours

Personal AI enhances efficiency by automating the export, transformation, and synchronization of legal data across management systems. This process not only streamlines operations but also significantly reduces non-billable administrative hours, freeing legal professionals to focus on revenue-generating activities.

Enable mission critical legal domain expertise across the enterprise.

Source of Truth

Consolidate various legal data from different systems into a unified repository to ensure alignment, establish training programs, and vet potential clients without having to spend your valuable hours while still maintaining your standards.

Collaboration and Transitions of Representation

Assist and collaborate with other professionals for comprehensive team-oriented legal strategies, particularly in complex litigation cases, and transitions.

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GET STARTED

Build with the AI that you own and is designed with your reputation and Identity in its mind.

Your own AI, a legally-tuned model, built to cater to your specific needs.

Streamlining Workflows

Personal AI automates the retrieval and analysis of legal documents, significantly reducing search time. It seamlessly integrates with firm systems, providing quick access to relevant case precedents and insights.

Enhanced Communication

The Personal AI platform facilitates enhanced communication within law firms by allowing lawyers to interact in natural language with the firm’s entire digital footprint. This feature supports more efficient internal collaboration, as lawyers can easily access shared knowledge from senior partners and previous cases, reducing the need for time-consuming meetings and discussions.

Innovate Safely and Responsibly

Personal AI ensures data privacy and security, adhering strictly to professional conduct rules. Each model is uniquely trained on the user’s own data, safeguarding sensitive information and maintaining client confidentiality. Access and use of client data is protected through the implementation of industry standard secure infrastructure like data encryption SOC 2, AES256 at rest, we use TLS 1.3 in transit with RSA key exchange, GDPR, HIPAA (Coming 2024) complying with legal and industry data protection standards.

What our clients say

“The beauty of the product is the high level of accuracy – again, because it is trained on MY data and not a large language model. “

Ed Diab

Founder, Diab | Chambers

“Personal AI is where we created our own original AI to educate lawyers on how we think, talk, and strategize.”

Robert Simon

Founder, The Simon Law Group

“Esquire Tek employs AI to streamline legal workflows, offering real-time assistance in objection handling, drafting, and compliance, enhancing attorney efficiency and service quality.”

Pratik Shah

CEO, EsquireTekAI

Personal AI for Legal

Meet Bob Simon:

The trailblazing trial attorney who's transforming mentorship with AI

Me and My AI:

Jacob Sapochnick
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Exploring the Differences Between Personal Language Models and Large Language Models

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