How to Choose a CLM for Law Firms (the UK, 2026)

Most contract lifecycle management (CLM) software was built for in-house legal teams managing one company's contracts, not for law firms advising clients. That single fact should shape how a firm chooses. A firm's return comes from recovered fee earner time on drafting, review and due diligence, and from quality and consistency across matters, not from tidying a single company's contract repository. Choosing well means weighting fit with matter-based work and AI analysis above the workflow features that dominate in-house CLM. This guide gives a UK law firm a practical way to choose contract and drafting software: the criteria that matter, a shortlist, and how to evaluate. It is general guidance, not legal advice. ## Start from the problems, not the feature list Name what costs the firm time and margin. Usually it is: fee earners spending hours on mechanical review, first drafts and bundle work; due diligence on a data room taking days of associate time; inconsistent drafting quality across the firm; and precedent knowledge locked in individual lawyers' heads. Modern AI tools address most of these directly. Your criteria come from the work the firm actually bills, so start there rather than from a generic CLM feature grid. ## The criteria that matter for a law firm Weight these: AI-assisted review and drafting that shortens the mechanical parts of client work; fast term extraction and due diligence across large document sets; per-clause risk flags that make review consistent; a structured clause and precedent capability that captures firm know-how; matter-linked files with a clean audit trail; and integration with your document management and practice management systems. Weight the data and ethics position heavily: whether the vendor trains models on your documents, confidentiality, and client-data handling, which are professional-conduct matters for a firm. De-weight the procurement and single-company workflow features that in-house CLM emphasises; they rarely fit a firm. ## Make your comparison criteria explicit and reproducible Do not choose on a polished demo. Define a test and run it on every shortlisted tool during a trial, scoring the same way. A good firm test: take a representative deal bundle or a defined contract set and measure how quickly and accurately each tool extracts key terms and flags risky clauses against a known answer key, how much it cuts review and due diligence time against your current baseline, how clean the first drafts are, and how well it fits matter-based working and your DMS. Record the scores. A reproducible evaluation is one you can put to the partnership. ## A shortlist worth testing Because most CLM is built for in-house teams, a firm's shortlist tilts towards legal-AI review and drafting tools and AI-native workspaces rather than procurement-led platforms. Options to evaluate include legal-AI review and due diligence tools used by UK firms, and AI-native workspaces such as Adira that combine drafting, per-clause risk and matter-linked files with transparent per-seat pricing. General in-house CLM such as Ironclad or Juro can serve a firm's own internal agreements but tends to fit client work poorly. Shortlist two or three that map to drafting and due diligence, and run the test. ## On pricing, model it against recovered time Most legal-AI and CLM vendors are quote-only. Favour those that publish pricing to anchor the comparison. As a transparent reference, Adira lists a Firm plan at 179 US dollars per seat per month billed annually, minimum five seats, roughly 141 pounds per seat per month at current rates (approximate; confirm current pricing on Adira's site), with a seven-day free trial. Set that per-seat cost against even a few recovered billable hours a week per fee earner and the economics are usually clear; model it against recovered time, not back-office savings. ## Make confidentiality and the training question a gate For a firm, the sharpest selection criterion is not a feature at all, it is how the vendor treats your clients' data. Any tool that processes client documents engages the firm's duties of confidentiality and its professional-conduct obligations, so make the data question a gate that a tool must pass before its features even matter. Ask every vendor directly whether it trains its models on your documents, and require a clear contractual no, because feeding privileged client material into a system that learns from it is a risk a firm cannot take lightly. Ask where data is stored, who can access it, and what security the vendor can evidence. A tool with brilliant review but an evasive answer on data should not make your shortlist, whatever time it would save, because a single confidentiality failure can cost a firm far more than any efficiency gain. ## Win the fee earners, not just the knowledge lawyers Firms often let knowledge lawyers or a small innovation group choose the tool, then wonder why fee earners do not use it. The people whose billable time you are trying to recover are the ones who must adopt the tool, so involve them in the choice. During the trial, put each shortlisted tool in front of the associates and paralegals who do the mechanical review and drafting, and let them use it on real matter work. Their verdict on whether it genuinely saves them time, and whether they trust its output enough to rely on it, is the truest signal you will get. A tool fee earners embrace recovers the billable hours your business case promised; a tool they tolerate and avoid recovers almost nothing, so weight their experience heavily in the final decision. ## A short bridge to one option If recovering fee earner time on drafting and due diligence is the goal, Adira is worth testing. It is built on Anthropic's Claude, does not train on your contract corpus, and brings AI drafting, a per-clause favourable, neutral or unfavourable risk view, plain-English clause editing with a diff, and matter-linked files and timelines into one workspace, with published per-seat pricing you can model today. As its own measured result, Adira reports that across 18 law firms using it, contract review and due diligence that took 10 to 12 days was cut to under two hours, with only two to three rechecks in total; treat that as Adira's figure and reproduce it on your own matters in the trial. It is India-first and expanding, so confirm your jurisdictions. You can see it at Adira. ## Bottom line A law firm should choose contract and drafting software on fit with matter-based client work, AI-assisted review and drafting, fast due diligence, per-clause risk, precedent capability, DMS integration and a sound data and ethics position, and should de-weight the procurement workflow features built for in-house CLM. Define a scored test on a real deal bundle with an answer key, run it across two or three tools in trials, measure the review and due diligence time saved against your baseline, and model the cost against recovered billable time. Decide on the evidence, because a number you reproduced is what persuades the partnership.