LEGAL AI CONSULTING
We help law firms and legal practices implement research-based AI solutions: available industry products, custom applications, and private AI designed around the needs of a particular firm or practice.
Start with the work, then choose the technology.
We draw on relevant research and engineering methods to implement AI around the documents, sources, decisions, and obligations of your practice. We translate those requirements into a technical design, evaluate the system against representative work, and plan for adoption.
The right approach may be an established industry product, a custom-built solution, private AI, or a combination. We help select, configure, integrate, and develop the capabilities that fit, with clear requirements for confidentiality, access, and human review.
AI Strategy & Implementation
We assess candidate workflows, compare platform capabilities, and identify the knowledge, access, and review requirements an implementation must satisfy. The resulting roadmap connects each proposed use of AI to a defined task, an accountable owner, and a way to judge whether it is helping.
Engagements can include platform selection, configuration, pilot design, and the practices needed to introduce AI into everyday work.
Legal Knowledge & Workflow Engineering
We connect relevant documents, firm knowledge, and business systems through workflows with defined permissions and responsibilities. Agents can prepare material, retrieve information, coordinate steps, and flag exceptions; the workflow specifies what they may do and when a person must review or decide.
Source references, review points, and records of activity help make the work inspectable as it moves between people and systems.
Private AI & Model Development
Some requirements call for closer control over models, information, and deployment. We help firms evaluate and develop private AI capabilities, including retrieval, model adaptation, and custom applications within an agreed technical environment.
Architecture decisions address where information is processed, who can access it, how it is retained, and how the system will be evaluated. We establish those requirements before choosing a model or deployment approach.
Evaluation & Ongoing Operations
We evaluate AI against representative tasks, source material, and explicit acceptance criteria. Tests examine whether outputs are supported, instructions are followed, permissions are respected, and uncertain or incomplete situations reach the appropriate reviewer.
As models, documents, and workflows change, we help maintain evaluations, review failures, and refine controls. Operational evidence should determine when to expand an agent’s responsibilities—and when to narrow them.
Define one workflow. Establish what good looks like.
A first engagement can focus on a single workflow: its inputs, expected outputs, access boundaries, and review requirements. We assess the available tools, build or configure a bounded pilot, and evaluate it against agreed criteria.
The result is a working basis for the next decision, including what is ready, what needs improvement, and what should remain with a person.