AI for Legal

Most AI tools for legal are either too generic or too complex, failing to address the specific operational drag on your firm. We build and manage custom AI employees that integrate directly into your case management and document systems to automate non-billable work and accelerate billable tasks.

Where AI actually moves the needle in legal

For many firms, the primary operational challenge is the volume of non-billable administrative work that consumes attorney and paralegal time. This includes tasks like client intake, conflict checks, and manually transferring information from emails or web forms into case management systems like Clio or PracticePanther. These processes are slow, prone to error, and create significant backlogs that delay client onboarding and matter initiation. The direct result is reduced capacity for high-value, billable work.

Document-intensive workflows are another major source of inefficiency. Drafting initial versions of standard documents—motions, discovery requests, engagement letters—relies on finding and adapting previous examples. Similarly, reviewing inbound contracts like NDAs or vendor agreements against firm standards is a repetitive task often assigned to junior associates. This work, while necessary, represents a significant time cost that directly impacts firm profitability and turnaround times for clients.

Knowledge management remains an unsolved problem. Years of valuable work product, legal memos, and expert opinions are locked away in document management systems like iManage or NetDocuments, or scattered across SharePoint sites and network drives. Finding relevant precedent or internal guidance requires cumbersome keyword searches and manual review. This makes it difficult for attorneys to access the firm's collective intelligence efficiently, leading to duplicated research and inconsistent work product.

Finally, the demands of e-discovery in litigation create immense data review burdens. Paralegals and contract attorneys spend thousands of hours on first-level document review, tagging for relevance, privilege, and key issues. This linear, manual process is not only expensive but also scales poorly with large data volumes, creating a bottleneck that can slow down case strategy and increase litigation costs for the client.

Six AI employees we deploy for legal teams

• Intake Specialist — Automates new client and matter onboarding. This AI employee processes intake forms from your website, extracts data from client emails, and creates new contact and matter files directly in Clio, PracticePanther, or your firm's CRM. It can run initial conflict checks against your existing database and notify the appropriate paralegal via Slack or email for final verification, reducing intake time from hours to minutes.
• Contract Analyst — Conducts first-pass reviews of standard agreements. It reviews inbound contracts (e.g., NDAs, MSAs, SOWs) against your firm’s pre-approved playbook of clauses. The AI flags deviations, missing clauses, and high-risk language, delivering a marked-up document and summary report for attorney review, typically reducing review time for standard agreements by 70-80%.
• Discovery Assistant — Performs initial document tagging and summarization. In our engagements, we connect this AI to e-discovery platforms to perform first-level review on large document populations. It tags documents for relevance, privilege, and confidentiality based on criteria you define, and can generate concise summaries of key documents, allowing human reviewers to focus on more nuanced analysis.
• Knowledge Management Aide — Surfaces internal precedents and expertise. This AI connects to your document management system (NetDocuments, iManage, SharePoint) to create a searchable knowledge base. Attorneys can ask natural language questions like, "Find our most recent motion to compel in a commercial dispute" or "What is our standard indemnification language for software vendors?" to instantly retrieve relevant documents and clauses.
• Drafting Assistant — Creates initial drafts of routine legal documents. Using your firm’s templates and approved prior work, this AI generates first drafts of common documents like engagement letters, simple motions, or discovery requests. The attorney provides key facts for the matter, and the AI assembles a complete draft in seconds, ready for human refinement and finalization.
• Billing Auditor — Reviews time entries for compliance and accuracy. This AI employee connects to your timekeeping and billing software (e.g., QuickBooks, TimeSolv) to audit time entries against client billing guidelines. It flags vague descriptions, block billing, or entries that violate outside counsel guidelines, reducing invoice rejection rates and improving billing hygiene before pre-bills are sent to partners.

A 90-day rollout plan

1. Phase 1: Discovery and Workflow Mapping (Weeks 1-2) Our engagement begins with a focused discovery process. We work with your partners, paralegals, and administrative staff to identify a single, high-impact workflow, such as client intake or NDA review. We map every step of the current process, identify the systems involved (e.g., web form, email inbox, Clio), and define the precise business outcome, like reducing client onboarding time by 50%. This ensures our first deployment targets a genuine pain point.
2. Phase 2: First AI Employee Deployed (Weeks 3-6) Using the workflow map from Phase 1, we build and train your first AI employee. For example, we would deploy our Intake Specialist, configuring it to parse your specific intake forms and emails. We launch it in a "human-in-the-loop" mode, where it processes live data but a designated paralegal validates its output before it commits data to your case management system. This builds trust and allows for fine-tuning based on real-world exceptions.
3. Phase 3: Integration and Second Workflow Discovery (Weeks 7-10) With the first AI employee validated, we deepen its integration. This might involve setting up automated Slack notifications for new matter approvals or connecting it to a conflict-checking API. Concurrently, we begin the discovery process for a second workflow, such as contract analysis. This parallel path accelerates the return on investment while the first employee is already delivering value.
4. Phase 4: Scaling and Governance (Weeks 11-13) In the final phase, we transition the first AI employee to more autonomous operation, with human oversight focused on exceptions rather than every transaction. We finalize the build of the second AI employee and establish a governance framework. This includes defining user permissions, creating audit trails, and providing training for your team to ensure they can manage and interact with their new AI colleagues effectively.

What good ROI looks like

The most immediate return is the reclamation of non-billable hours. A well-deployed AI employee for administrative tasks like intake or billing audit typically saves each participating paralegal or attorney between 5 and 10 hours per week. This time is directly reallocated to billable work, increasing firm capacity without increasing headcount. For a small team, this can be the equivalent of hiring an additional part-time administrative assistant.

We also measure ROI by the reduction in cost per task. A junior associate might spend one billable hour reviewing a standard 10-page NDA, costing the client or the firm $250-$400. An AI Contract Analyst can perform a more consistent first-pass review against your playbook in under five minutes. This allows the associate to focus their review on the flagged exceptions, reducing their total time on the task to 10-15 minutes and dramatically lowering the effective cost.

Improved velocity is another key metric. For client-facing processes, speed matters. Firms we work with often reduce their client intake and conflict check process from an average of 24-48 hours to under 2 hours. For transactional work, generating a first draft of a standard agreement can go from a multi-hour task to a 10-minute exercise. This improved responsiveness enhances the client experience and increases the firm's overall throughput.

Compliance, data, and risk

We understand that data confidentiality and attorney-client privilege are paramount. Our solutions are designed with a security-first architecture. We deploy AI employees in single-tenant, private cloud environments, ensuring your data is never co-mingled with other clients' data and is never used to train public models. For firms with specific data residency requirements or a preference for on-premise infrastructure, we can deploy our solutions directly within your existing data center.

To protect sensitive information, we implement multi-layered safeguards. All data in transit and at rest is encrypted using industry-standard protocols. We configure PII and privileged information redaction pipelines that automatically identify and mask sensitive data before it is processed by the AI models. Access to the AI systems is governed by strict role-based access controls (RBAC), mirroring the permissions within your own firm. Every action taken by an AI employee and every query made by a user is recorded in an immutable audit log, providing full transparency and traceability for compliance and review.

Human oversight is a core component of our risk mitigation strategy. For sensitive workflows like document review or legal drafting, our systems are designed to produce drafts and recommendations for human verification. The final legal judgment always rests with a qualified attorney. This human-in-the-loop approach ensures quality and accountability while still gaining the significant efficiency benefits of automation.

Common objections we hear

• "AI will compromise client confidentiality." We address this by using private, isolated environments for each client. Your data is not used for any purpose other than powering your specific AI employees, and we offer on-premise deployment for maximum control.
• "This will replace our junior associates and paralegals." Our goal is to augment, not replace. We automate the repetitive, low-value tasks, which frees your legal professionals to focus on strategic, high-judgment work that clients value and that builds their expertise.
• "Our firm's processes are too specialized for a standard tool." We agree, which is why we don't sell a one-size-fits-all product. Our entire process is built around discovering your unique workflows and configuring custom AI solutions that fit how your team already works.
• "We don't have the budget or IT staff for a major technology project." Our 90-day phased rollout is designed to be manageable and prove value quickly with a single, affordable project. We manage the AI infrastructure, so it doesn't create a new burden for your IT team.

Frequently asked questions

How does AI integrate with Clio or PracticePanther?

We use the official APIs (Application Programming Interfaces) provided by case management systems like Clio, PracticePanther, MyCase, and others. This allows our AI employees to securely read and write data, such as creating new contacts, opening matters, and uploading documents, just as a human user would, but automatically.

Can your AI draft legal documents from scratch?

Our AI does not "create" novel legal arguments. Instead, it acts as a very advanced document assembly tool. We train it on your firm's best work product and templates. It then uses that knowledge to generate a first draft of a routine document based on the specific facts of a new matter, which is then reviewed and refined by an attorney.

What data is needed to train a legal AI model?

For a workflow like contract review, we would need a collection of your existing agreements and your firm's playbook or review guide. For a knowledge management AI, we would index your document management system. The quality and organization of your existing data are important, and our discovery phase helps assess what is needed.

Is the AI's work product reliable for legal use?

The AI's work product should be considered a high-quality first draft or a recommendation, not a final, filed document. The system is designed to be supervised by a qualified attorney who is responsible for the final work product. Its reliability for a specific task is proven during the human-in-the-loop validation phase of our rollout.

How long does it take to see a return on investment?

Most firms begin to see a tangible ROI within the first 90 days. By automating a single high-frequency workflow, such as client intake, the time savings for the administrative or paralegal team are immediate. The payback period for the initial investment is typically between 6 and 12 months, depending on the volume of the automated task.