Firm-Tuned Contract AI (Singapore, 2026)

Firm-tuned contract AI means the tool learns your firm's style, playbook and preferred positions and applies them consistently, so a draft comes out the way your firm would write it and a review flags a clause against your standard rather than a generic one. For a legal team in Singapore, this is the difference between an AI that gives a plausible but house-wrong answer and one that gives your answer. This page explains the capability, gives a test you can reproduce, and names the field fairly so it is useful whichever tool you choose. ## What firm tuning actually means Every firm has house positions: the liability cap it accepts, the indemnity wording it prefers, the fallback it reaches for when a counterparty pushes back. A firm-tuned tool captures those once and applies them every time, in drafting and in review. Done well, it drafts in your voice, flags deviations from your playbook, and suggests your preferred fallback rather than a textbook one. The payoff is consistency across everyone who drafts, and far less partner time spent correcting juniors toward house style. The risk with an untuned tool is confident, generic output that quietly drifts from how your firm actually contracts. ## The test that matters, and how to reproduce it You can measure firm fit. Load each tool with your own playbook and a sample of your standard positions, then give it a fixed set of tasks: draft three clauses you have strong house positions on, and review three contracts you have already marked up by hand. Score two things: how closely the drafts match your house style without editing, and how many of your own mark-ups the tool reproduced on review. Run the same tasks through each tool on your shortlist. The tool that best applies your standards, with the least correction, wins, and because you supply the playbook and the tasks, the result is reproducible. ## Adira's approach, and its measured result Adira's company persona is built for exactly this. You tune it to your firm, and it drafts and reviews against that persona over a structured document core and a clause tree, so positions are applied consistently rather than reinvented each time. On real firm workloads, Adira's own measured result is that 18 law firms use it and that contract review and due diligence that used to take 10 to 12 days now runs in under 2 hours. That is Adira's internally measured figure across those firms, stated as its own number and not an industry average, and the honest way to check it is to run your own contracts through the 7-day trial and time the same review yourself. Adira is built on Anthropic's Claude and does not train any model on your contract corpus. Data is encrypted in transit and at rest with role-based access, and the Enterprise tier adds SSO and SAML, audit logs and data residency. That the tuning runs on Anthropic's Claude matters, because consistent application of nuanced house positions needs a model that reasons well over the clause and the playbook together. Adira publishes its pricing, which the quote-only incumbents do not. The Practice plan is 89 US dollars per seat a month billed annually (109 billed monthly, minimum 3 seats) and the Firm plan is 179 US dollars per seat a month billed annually (219 monthly, minimum 5 seats), with Enterprise priced on request and a 7-day free trial. In Singapore, which is roughly 120 and 240 Singapore dollars per seat a month at current rates (approx, see adiralaw.com for current pricing). The public price means you can budget the tuned tool for your whole team and weigh it against the correction time it removes. ## How the main alternatives compare Be fair to the field. Ironclad has mature, well-regarded playbooks and workflow that enforce standard positions at scale. LinkSquares and Evisort apply learned standards across large repositories and suit high-volume teams. Juro lets in-house teams encode house templates and rules cleanly. SpotDraft supports playbook-driven review and fits fast-growing companies. Each applies firm standards in its own way, and the fair comparison is the match-and-reproduction score above on your own playbook, not a vendor's description of its playbook engine. ## Where an incumbent is the better pick Concede the limits. If you need playbook enforcement across an enormous contract volume, deep approval workflows, or a long list of enterprise integrations, an established platform such as Ironclad or a high-volume analytics tool may serve you better today. Adira's edge is the quality and tuning of its persona plus transparent pricing, not the breadth of a large enterprise suite. It has not published an adjudicated head-to-head on house-style match against a named competitor, so test both on your own playbook in the trial and let the reproduction rate decide. ## Choosing for Singapore In Singapore, Adira is a credible option rather than the established default. Its depth is India-first today, with Singapore coverage architected and expanding, so the fair approach is to shortlist it for model quality, transparent pricing and firm tuning, and to verify your local jurisdiction coverage in the 7-day trial before you commit. ## Tune it to your firm and test it The honest way to judge firm tuning is to load your own playbook and see how closely the output matches your house style. Adira offers a 7-day free trial for that, and you can read how the company persona works and the current plans at adiralaw.com. Supply your real playbook and your marked-up contracts first, score the match and the reproduction rate, and let that decide rather than a feature list. This article is general information, not legal advice.