Question 1

How does an AI engineering retainer for legal preserve attorneyclient privilege?

Accepted Answer

Privilege is engineered at the architecture layer. Retrieval systems enforce tested matterisolation boundaries so a query in one matter cannot reach another matter's work product. Prompts touching matter data keep privileged content inside the firm's controls, with onpremise deployment where required. Every retrieval is logged by matter, user, and query. Because one team builds every system, the privilege model is consistent rather than varying per vendor.

Question 2

Can the firm satisfy client security audits and outsidecounsel guidelines with this?

Accepted Answer

Yes, and that is much of the point. The retainer produces the documentation a client security questionnaire asks for: access controls, audit logs, datahandling design, and deployment model. Because one team is accountable for every system, the firm gives clients one coherent, current answer instead of assembling responses from multiple vendors.

Question 3

Does this replace the firm's lawyers' judgment on ethics and privilege?

Accepted Answer

No. Bitontree is an AI engineering firm, not a law firm. The retainer builds the systems and the technical evidence; the professional judgment about privilege, conflicts, competence, and ethics stays with the firm's attorneys and risk leadership. The retainer's value is building to that judgment consistently and giving the firm the record to stand behind it.

Question 4

Which legal practice tools can the team integrate with?

Accepted Answer

The team integrates with common practice platforms including Clio, MyCase, and NetDocuments, covering matter management, document storage, intake, and billing. The architect maps the firm's matterdata model during discovery so confidentiality boundaries are correct before any system is built.

Question 5

Can we start with one system and expand later?

Accepted Answer

Yes, and most firms do. An engagement typically starts with one system, often legal research, and expands once the privilege architecture is proven. Because that architecture is built once and inherited, each additional system ships faster and lowers cost per system as the engagement grows.

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AI Engineering Retainer for Legal: Build Privilege-Safe AI Across Research, Documents, and Matters