Solutions · Legal & compliance
Legal work that scales without lowering the bar.
Legal and compliance teams are asked to review more contracts, answer more questions and track more regulation with the same headcount. AI agents take on the first pass, the retrieval and the monitoring, so qualified people spend their time on judgement, negotiation and risk. Every output that leaves the department is approved by a lawyer.
Where agents pay off in legal
Most legal work is reading, comparing and looking things up. That is exactly what language models do well, provided a lawyer stays in charge of the conclusion.
An in-house legal team of three at a mid-sized company sees hundreds of NDAs, supplier agreements and data-processing agreements a year, answers a constant stream of "can we do this?" questions from the business, and is expected to know what changed in the EU AI Act, the GDPR, NIS2 and product regulation last month. None of that is optional, and very little of it is where legal expertise creates the most value.
AI agents change the economics. They read an incoming contract against your playbook and flag the deviations, extract obligations and deadlines into a register, answer policy questions for employees with citations to the actual policy, and summarise regulatory changes for the compliance officer. The lawyer reviews a structured first pass instead of a blank page.
The constraints are stricter than in most departments: confidentiality, professional secrecy, legal privilege and the fact that a wrong answer can create liability. That is why our legal deployments start with internal use cases, run on infrastructure that satisfies your confidentiality requirements, and keep a lawyer's approval in front of anything external.
- Typical starting pointNDA and DPA first-pass review
- Human checkpointLawyer approves every external output
- SystemsCLM, DMS, SharePoint, email, ticketing
- HostingEU cloud or on-premises where privilege demands
Use cases
Six workflows we see legal and compliance teams start with. Each names the systems involved and where the human decides.
Contract intake and first-pass review
Incoming NDAs, supplier agreements and DPAs arrive by email or through a request form. The agent classifies the contract, compares each clause against your playbook, flags deviations with the reason and proposes fallback language. The lawyer reviews the marked-up draft and decides what to negotiate.
Clause extraction and obligation tracking
From signed contracts in your DMS or CLM, the agent extracts parties, terms, renewal dates, notice periods, liability caps and obligations into a register. Reminders go to the business owner before deadlines. Legal spot-checks the extractions; nothing is changed in the contract itself.
Legal knowledge assistant for the business
Employees ask questions such as "can we share this customer list with a partner?" and get an answer drawn from your policies, precedents and guidance notes, with citations and a clear escalation when the question needs a lawyer. Permission-aware: privileged material stays with legal.
Regulatory monitoring
The agent watches sources you define, such as official journals, regulators and law-firm briefings, and produces a weekly digest of changes relevant to your sectors, with a suggested impact rating. The compliance officer decides what becomes an action item.
Compliance case documentation
For whistleblowing cases, incident reports and audit requests, the agent assembles the timeline, collects the relevant documents and drafts the case file structure. Investigators and counsel do the assessment; the agent only organises.
Data-subject request support
When a data-subject access request arrives, the agent identifies the systems likely to hold the person's data, drafts the search queries, compiles results for review and prepares the response letter from your template. The data protection officer checks and sends.
A worked example
NDA review from inbox to signature
The most common first deployment in legal is a review agent for non-disclosure agreements, because volume is high, the playbook is usually already written, and the risk of a bad outcome is contained. Here is how the workflow runs in practice.
- A counterparty's NDA arrives in the legal mailbox or through the request form. The agent recognises it as an NDA, extracts the parties, the governing law and the term, and checks whether the counterparty already has an active agreement in the CLM.
- The agent compares each clause against the playbook: definition of confidential information, permitted purpose, term and survival, residual knowledge, non-solicitation, governing law, injunctive relief. Each deviation is marked with the playbook position and a proposed fallback clause.
- The result is a redlined document and a one-page summary: what is acceptable, what needs negotiation, what is a hard stop. The summary states the agent's confidence for each finding.
- A lawyer reviews the summary and the redline. Routine deviations are accepted or negotiated with one click; unusual clauses are read in full. Nothing is sent to the counterparty without this review.
- After signature, the agent files the executed NDA in the CLM, records term, notice period and counterparty in the obligation register, and sets the renewal reminder.
- Every step is logged: which document was read, which playbook version was applied, what the agent proposed and what the lawyer changed. That log is the basis for improving the playbook and for demonstrating oversight.
Guardrails for legal and compliance
A lawyer approves everything external
Contracts, letters, responses to authorities and advice to customers are drafted by the agent and released by a qualified person. The agent's confidence score determines how much attention a draft gets, never whether it gets any.
Confidentiality and privilege drive the hosting decision
Privileged material and sensitive investigations may require models that run in the EU or on your own infrastructure, with no training on your data and contractual guarantees from the provider. We map your confidentiality classes to hosting options before choosing a model. See our guide to sovereign AI and EU-hosted models.
No legal advice to customers by an agent
Agents may answer internal policy questions with citations. They do not give legal advice to external parties, and internal answers carry a clear "escalate to legal" path when the question exceeds the policy.
Playbooks and policies are the source of truth
The agent applies your documented positions. Where no position exists, it says so rather than inventing one. That makes gaps in your playbook visible, which is useful in itself.
Audit trail by default
Every review, extraction and answer is logged with source documents and model version. Regulators, auditors and your own quality reviews can reconstruct what happened.
How we start
Assess
Two to three weeks: we map contract volumes and types, existing playbooks, systems (CLM, DMS, email), confidentiality requirements and the questions the business asks most. Output: two or three ranked use cases with a business case and a hosting recommendation.
Design
Playbook formalisation with your lawyers, definition of the approval workflow, data-protection review with your DPO, and, where relevant, works council involvement. We specify the guardrails before writing a prompt.
Pilot
Six to eight weeks to a production-grade agent on one contract type or one knowledge domain, evaluated against a set of real past contracts with known outcomes. Lawyers use it on live work from week four.
Scale
Extend to further contract types, the obligation register and regulatory monitoring. Train the team to maintain playbooks and read the agent's logs. Optionally hand over to managed AI operations.
Frequently asked questions
How accurate is first-pass contract review?
Good enough to be useful, not good enough to be unsupervised. Against a well-written playbook, an agent finds the large majority of deviations and occasionally flags something that is fine. That is why a lawyer reviews the summary and the redline. We measure recall and precision on your own past contracts during the pilot and report the numbers, so you know what the agent misses.
Can we use this with privileged or highly confidential documents?
Yes, if the hosting matches the sensitivity. Options range from EU regions of major cloud providers with contractual no-training guarantees to models running entirely on your own infrastructure. We classify your material first and choose accordingly. Some categories, such as active litigation files, may stay out of scope by design.
Does the agent replace external counsel?
No. It reduces the volume of routine work that reaches both your in-house team and your outside firm. Complex negotiations, litigation and regulatory strategy remain with lawyers. Many teams use the agent to prepare better briefs for outside counsel, which reduces hours on the invoice.
How does this interact with the GDPR and the EU AI Act?
Contract review and policy Q&A involve limited personal data and are generally low-risk under the EU AI Act, but the data-protection assessment still has to be done, and employee-facing assistants may need works council involvement in Germany. Our governance service handles the classification and documentation with your DPO. This is consulting, not legal advice.
What happens to the legal team's jobs?
The reading and sorting moves to the agent; the judgement stays with people. In practice legal teams take on work they previously outsourced or declined, and turnaround times for the business improve. Where the workload changes materially, we plan the transition with the team rather than around it.
Which systems do you integrate with?
Contract lifecycle management and document management systems, SharePoint and Confluence, email and ticketing tools, and e-signature platforms, through their APIs or, increasingly, the Model Context Protocol. We check the concrete systems during the assessment.
Related
AI governance, EU AI Act & GDPR
An AI register, risk classification under the EU AI Act, GDPR-aligned processes and a usage policy your teams will actually follow, built together with your lawyers and your data protection officer.
Enterprise knowledge assistants (RAG)
Assistants that answer from your SharePoint, Confluence, DMS, ERP and ticket history: permission-aware, with citations, evaluated, hosted in the EU.
AI agents for procurement
Request intake, RFQ drafting, quote comparison, supplier onboarding checks and spend analysis, with buyers approving every award and every order.
Professional services
Proposals, research, document review and knowledge management for law firms, tax advisors, consultancies and agencies, under professional secrecy.
Let's find the first workflow worth automating.
A 30-minute intro call, no slides and no obligation. We listen, ask about your processes, and tell you honestly where AI agents would pay off and where they would not.