Sector · Law firms
More time on the merits, less on research.
In law firms, hours go into document research, repetitive drafts and deadline management. AI prepares the groundwork; the decisions and signatures remain yours.
Case files, drafts, deadlines.
AI prepares the supporting documents; professional judgement remains human.
Common problems
Valuable hours spent searching, not reasoning.
Documents to review, case files to summarise, drafts repeatedly written from scratch and deadlines that cannot be missed. AI can prepare this work, freeing the firm's most qualified people to exercise their professional judgement.
Practical use cases
Four ways to free up hours.
Document search
Find the right clause, precedent or passage in your firm's archive in seconds, with a source citation.
Drafts of standard legal documents
First drafts of contracts and recurring legal documents, pre-filled with case data. You review and tailor them.
Case file summaries
Summaries of lengthy case files and correspondence, so you can get up to speed on a case in a few minutes.
Deadlines and hearings
Procedural deadlines and obligations are tracked, with automatic reminders sent to the relevant people.
Expected results
More cases, the same care.
- Document searches that take minutes rather than hours, with sources always cited.
- Drafts of standard legal documents, ready to review instead of writing from scratch.
- Deadlines and time limits are monitored, reducing the risk of omissions.
- Handle more cases while maintaining quality.
Responsibility
AI proposes; the lawyer decides. Every draft cites its sources, and all data is handled in line with professional confidentiality and GDPR.
In summary
Theartificial intelligence for law firms does not make decisions or sign documents: it prepares the groundwork. It searches case files, summarises legal documents and rulings, and prepares first drafts of contracts and submissions — always as material to review, with sources cited. Responsibility remains with the lawyer.
This is where legal tech changes a law firm's working day: hours spent on document research, repetitive drafting and deadline monitoring become available for substantive legal work and clients.
We start with an audit of your firm's processes: measure where the hours go, identify the workflows with the highest return, and introduce AI in line with GDPR and professional confidentiality. We address the most time-consuming use case first, then the rest, measuring results in hours freed.
FAQ
Questions from accounting firms.
Yes, if used without checking. That is why every output is a draft with clearly identified sources, intended for a lawyer to review. AI speeds up the first draft and research; responsibility always remains human.
With GDPR-compliant tools, European servers where possible, and data that is not used to train external models. Professional confidentiality is a project requirement, defined before work begins.
Yes. The assistant works with your documents and precedents. It cites your firm's source materials in its answers, so you can verify every statement.
With document search and case file summaries: these are the tasks that consume the most hours and where AI offers an immediate advantage, while keeping the lawyer in control.
Summarise case files and legal documents, search your documents and precedents, draft contracts and communications, extract clauses and deadlines, and sort correspondence. Everything is provided as a draft with clearly identified sources, ready for a lawyer to review.
We start with a fixed-price audit measuring the hours spent on research and drafting, then set up the first assistant. You know the cost in advance; it pays back through the hours your firm recovers on each case.
Legal tech covers tools — including AI — that digitise and automate legal work: research, document management, assisted drafting and deadline tracking. The aim is to save lawyers time on repetitive tasks, rather than replace them.
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No risk to confidentiality
Let’s find the first task to simplify.
On a call, we define a practical use case and the confidentiality requirements before writing a line of code.