AI Governance for Law Firms and Legal Teams.
Associates, partners, paralegals, and in-house counsel are sending privileged communications, deal documents, deposition transcripts, and matter material into ChatGPT, Copilot, Harvey, and internal AI tools. The gateway between those users and the model is where ABA Model Rule 1.6 confidentiality, Rule 1.1 competence, and the outside counsel guidelines clients impose on the firm need to be applied, because the content control plane the LLM provider offers stops at the model boundary and is blind to the firm policy.
DeepInspect runs inline in front of the AI provider. Privileged material, client identifiers, matter codes, and work product are detected and transformed before the payload leaves the firm environment. Every decision is written to a tamper-evident forensic record with the policy version, the actor identity, the matter context, and the original and transformed payloads preserved. The same configuration applies to interactive chat, retrieval-augmented research tools, and autonomous agent workflows that touch the document management system.
The risk surface in legal AI
Privileged content inside prompts
Lawyers paste privileged communications, deal documents, deposition transcripts, and client memos into AI tools to summarize, classify, or draft. Once that payload leaves the firm boundary, the LLM provider terms of service are the only remaining control. Those terms cover retention and downstream training. They do not preserve privilege.
Fabricated citations in filings
Mata v. Avianca made fabricated AI citations a sanctions matter in mid-2023, and the running count of follow-on sanctions decisions has grown into the hundreds across federal and state courts. The supervision failure that the courts cite is the absence of a verification step before the filing went out the door.
Ethical-wall and conflict-of-interest enforcement
Ethical walls are enforced at the DMS layer. The AI gateway is a parallel egress path that the wall has not historically covered. An attorney on a screened matter can prompt with conflicted-client data the moment the policy stops at the DMS, because the AI tool does not see the screen.
Outside counsel guidelines and client audit
Major clients now write AI usage clauses into outside counsel guidelines and ask the firm to evidence the controls during the annual audit. Most firms are unable to produce the contemporaneous record because the AI interaction log either does not exist or sits inside the LLM provider in a form the firm cannot retrieve.
How DeepInspect applies controls
Privilege and work-product detection
Deterministic detectors match privilege markers, client identifiers, matter codes, work-product patterns, and deal-codename lists supplied by the firm. Each match is redacted, tokenized, or blocked according to the configured action for the role in effect. Tokenization keeps a reversible mapping inside the firm environment so responses can be re-hydrated for the attorney.
Matter-aware policy and ethical walls
The firm IdP and matter-management system supply identity and matter context at request time. The gateway evaluates the per-matter action map and applies the matching transformation. An attorney on a screened matter is blocked from prompting with conflicted-client data even when the attorney has DMS access elsewhere.
Citation verification on model outputs
Output-side detectors flag legal citations in model responses and route them through an internal verification pipeline before the attorney sees the final draft. The decision, the flagged citations, and the verification outcome are preserved in the forensic record, which gives the firm the supervision evidence ABA Formal Opinion 512 and the sanctions case law have established.
Evidence-grade forensic record
Every interaction writes a signed record containing the actor identity, the matter context, the policy version, the rule evaluation path, the original payload, the transformed payload, and the upstream response. The record set is queryable by the General Counsel, the Risk Officer, and the client during an outside counsel guidelines audit.
Prompt injection and adversarial input handling
Adversarial inputs inside opposing-counsel filings, deposition exhibits, and discovery productions are scored against the configured detectors and blocked or routed to escalation according to policy. The score, the input, and the action are preserved in the forensic record.
Tool and agent allowlists for the DMS and research platforms
Autonomous agents reach the DMS, billing system, and legal research platforms. The gateway enforces allowlists and blocklists on the tools an agent invokes and the data sources it reads. An agent that attempts to call a system outside its allowlist is stopped at the gateway with a record of the attempt.
Professional responsibility mapping
ABA Model Rule 1.6 Confidentiality
The gateway enforces the confidentiality boundary at the AI request layer. Client identifiers and privileged content are blocked or tokenized before the payload leaves the firm. The forensic record evidences the reasonable efforts the rule requires.
ABA Model Rule 1.1 Competence
Comment 8 imposes a duty of technological competence, which ABA Formal Opinion 512 extends to generative AI. The output-side citation verification and the supervision audit trail support the competent-use obligation the rule contemplates.
ABA Formal Opinion 512 (2024)
The opinion sets expectations on confidentiality, communication with clients, supervision of associates and non-lawyer staff, and fees when generative AI is used. The gateway record covers the supervision and confidentiality evidence the opinion contemplates.
State bar AI ethics opinions
Opinions from the New York State Bar, California, Florida, and Texas track the same themes: confidentiality, competence, and supervision. The gateway record is a single artifact that addresses the evidence layer across jurisdictions.
Outside counsel guidelines
Client AI clauses ask for evidence of policy, training, restriction on data classes, and an auditable record of usage on the client matter. The matter-aware audit trail produces the artifact the annual client audit asks for.
The scale of the gap
legal decisions worldwide have now addressed fabricated citations or hallucinated authority generated by AI tools, with the count growing every month since Mata v. Avianca in 2023.
of large law firms have adopted AI tools in some part of their practice, while client-imposed governance and audit obligations have run ahead of internal controls at most firms.
Source: Thomson Reuters, Future of Professionals Report 2024.
of organizations reported confirmed or suspected AI agent security incidents in the past year. Law firm AI adoption shares the same risk surface with the added overhead of privilege and matter-conflict obligations.
of builders cite the absence of auditability and logging as a top concern. Only 7.7% audit agent activity daily, which leaves most firms without the contemporaneous record outside counsel audits and bar disciplinary inquiries expect.
Deployment
The gateway runs self-hosted in the firm VPC or on-premises. SaaS and hybrid deployments are available for firms with different sovereignty requirements. Privileged content, the forensic store, and the transaction object store stay inside the firm boundary in every configuration.
DeepInspect sits inline between users, agents, and the AI provider. It works with OpenAI, Azure OpenAI, Anthropic, Bedrock, internal models, and vertical legal tools that proxy through the firm gateway. Existing IdP, DMS, matter-management, and conflicts-system integrations stay in place. Production cutover typically lands inside two weeks for a defined practice scope.
Policy on every AI interaction, enforced before privileged data leaves the boundary.