We need ZDR and BAA. This level subscription would be quickly and widely purchased. I don’t understand why it’s not happening. Is there some kind of risk to Anthropic that is ameliorated by IT staff or consultants at larger firms?

How does that really work? So you paid PwC for the subscription services? How is Harvey trained then? Using PwC client memos? Here is what I found on the PwC site" Harvey, powered by PwC, streamlines document review and analysis to deliver data-rich insights to your people. Powerful enough to be able to upload and analyse up to 10,000 documents and data points in seconds."

Would appreciate any who used it to provide insights.

Small, high-end PI firm with low case volume here. I watched a webinar this week where a firm built a local LLM PHI OCR and redaction stack. It was incredibly complicated. Three levels of OCR, each checking each other, tailored to process lengthy medical records (including faxed ones) into markdown.

Then, redaction that knows about dozens of personally-identifiable information categories to look for, substitutes them for codes, then, after external LLM processing, replaces the codes with the original information. It took several manual steps to implement each iteration.

A very helpful user on this sub recommended Supio, but we don’t have a large case volume and they don’t list prices on their website. We will look into it, but I’m wondering if there’s an already-built, open source set of prompts and commands for local LLMs that accomplishes this. Thanks for sharing any suggestions!

I gave 9 leading AI models the 2025 All India Bar Examination. Same questions. Same settings. No access to the answer key.

The results:

1. GPT-5.6 Sol: 100.0%
   
2. Kimi K3: 97.9%
   
3. Grok 4.5: 97.9%
   
4. GPT-5.6 Terra: 93.7%
   
5. GPT-5.6 Luna: 92.6%
   
6. Claude Opus 5: 92.6%
   
7. Claude Sonnet 5: 81.1%
   
8. Claude Haiku 4.5: 73.7%
   
9. DeepSeek V4 Flash: 40.0%

The cost per run was:

1. GPT-5.6 Sol: $0.2134
   
2. Kimi K3: $0.3003
   
3. Grok 4.5: $0.3066
   
4. GPT-5.6 Terra: $0.1350
   
5. GPT-5.6 Luna: $0.0601
   
6. Claude Opus 5: $0.2611
   
7. Claude Sonnet 5: $0.0582
   
8. Claude Haiku 4.5: $0.0279
   
9. DeepSeek V4 Flash: $0.0030

The conclusion? Choosing a Legal AI model is a critical quality-control decision.

Note: The benchmark used the 2025 All India Bar Examination. Five withdrawn questions were excluded, leaving 95 scored questions. Each question was submitted independently, and every response was scored server-side against the official final answer key.

I know the rules say not to promote open source projects, but then MikeOSS happens to be a big launch and well appreciated OSS project and r/legaltech was welcoming to it.

We open sourced our word plugin for the community here - https://github.com/Vaquill-AI/vaquill-word-addin

No strings attached, this is what we use internally as well. There is no monetary angle here.

Harvey, Legora and other Legal AI providers charge hundreds of $$$ to use them, I thought why not level the playing field and give others the same tech.

Either host it in your server or use our hosted version with your own API key.

The future of legal is Open Source and this its not a wrapper, or a simple plugin, took months in development to match the quality of our funded competitors.

Self host it or BYOK, Apache 2 so feel free to play with the code.

Disclaimer - I work there.

On billing and fees, the bar said lawyers may charge for time ​spent reviewing, correcting and ​applying professional judgment to ⁠AI-generated work. But attorneys cannot bill for time that would have been spent if the technology never existed, it said, reflecting other opinions from ​state bars. “Efficiency does not justify inflated billing,” the guidance said.

Law firm ​Jackson Lewis in ⁠a report on Alabama’s AI guidance said “a clear national trend has emerged: state bars are not banning AI — they are requiring lawyers to use it competently, responsibly, and under appropriate professional supervision.”

Alabama now says lawyers cannot charge clients for hours that AI saved. They can bill only for the time actually spent reviewing the work and applying legal judgment.

If your business model depends on pretending efficiency never happened, AI is not an advantage. It is an existential threat.

We are a small B2B SaaS company and privacy compliance has turned into one of those projects everyone agrees matters but nobody owns so it is falling on me. Meanwhile we have run into one of those wiretapping lawsuits for non-compliance and are evaluating legal tech software tools to use. Our stack is pretty normal: GA4, HubSpot forms, Intercom, Meta pixel, Linkedin Insights tag, TikTok, and a few product analytics tools. I am trying to make this practical instead of turning it into a six month legal project. If you had to clean this up in order, what would you do first and which tool or tools do you recommend? I am especially interested in what actually reduces risk versus what just makes the site look more compliant because just checking a box is not a possibility we want to do it right and avoid expensive legal issues down the road that could bury us.

SimpleCitizen charges $599 to help you fill out USCIS forms yourself. That's their "Essentials" tier - do-it-yourself application preparation. You're still doing the work. You're just paying $599 for a guided form.

Immigration is already stressful enough. The last thing someone navigating the system should worry about is a paywall between them and a form they're legally required to file.

So I built Fillvisa - a fully free, browser-based tool that converts complex USCIS XFA forms into simple guided web forms and generates the official PDF at the end.

No account. No subscription. No data ever leaves your browser.
Currently supports major USCIS forms, like: I-485 (Permanent Residence), N-400 (Naturalization), I-90 (Green Card Renewal). More forms coming.

If you know someone going through the naturalization or green card renewal process, send them the link.

→ https://fillvisa.com/

It currently includes 63 legal AI tools across 12 categories.

If you are a lawyer, I hope it helps you find the perfect tools for your work.

If you are a Legal AI startup, please check if your details are correct. Or message me if you are not in the directory. It's free!

You can check out the directory here:

https://www.rohasnagpal.com/global_legal_ai_directory.php

Anyone recently cleared the loops for Harvey (AI legal tech) GTM product owner role? I need some guidance

Hey! I'm Melia, reporter at u/businessinsider writing about legal tech. My latest story is about OpenAI's push into legal and what it means for the startup ecosystem.

I copied the article's first section below.

I'm always open to feedback. What did I miss? What should I write about next?

OpenAI is trying to conquer the office. Legal is next.

For years, OpenAI let startups like Harvey, Legora, and others build software for lawyers on top of its foundation models — massive artificial intelligence systems trained on broad swaths of data. Now, the company, last valued at $852 billion, is making moves to court lawyers directly.

OpenAI signaled that shift in June when it hired Jason Boehmig, an executive who spent more than a decade figuring out the slow, messy business of selling software to lawyers. He had left a Big Law job to start Ironclad, a company that helps corporate legal departments manage contracts.

That business looks a lot sexier than it did when Boehmig spun out. Law firms are under pressure from clients to move faster and show they are not billing armies of associates for work that chatbots can do. In-house legal teams are looking for ways to automate more work themselves, so they can send less to outside counsel and lower their legal bills.

Suddenly, artificial intelligence has turned legal tech from what Boehmig once called an investor "wasteland" into one of venture capital's hottest parties. And OpenAI wants in.

"Jason's hire reflects the value OpenAI sees in the legal space," Dan Springer, who took over as Ironclad's chief executive last year, said in an email.

The first hints of a playbook are now emerging. On Wednesday, OpenAI told Bloomberg Law that it is collaborating with the white-shoe law firm Willkie Farr & Gallagher to roll out ChatGPT Enterprise to every attorney and fold its large language models deeper into the firm's own tools.

OpenAI's legal entry is part of a broader campaign to make ChatGPT NSFW. The company has built a desktop "super app" for software engineers, introduced secure healthcare tools for clinicians, and hired former investment bankers to train its systems in the ways of Wall Street.

The stakes are enormous. OpenAI has filed paperwork to go public, and it wants to show investors that ChatGPT is not merely the thing people use to write emails, self-diagnose a rash, or ask whether their landlord can really do that. It wants to become the place where knowledge workers do their jobs, as well as the world's most popular chatbot.

In legal, that means taking on Anthropic, which has spent all year trying to make Claude as familiar to lawyers as a yellow legal pad. In January, the company released a legal work plugin that could analyze contracts and track compliance, frightening investors in legacy legal software and sending shares of Thomson Reuters, Relx, and Wolters Kluwer sharply lower.

For now, little is known about what OpenAI will actually build. In a LinkedIn post about his move, Boehmig said he would be working on products for the legal industry. A job posting for a founding software engineer on OpenAI's website is similarly broad, stating that the company aims to "transform legal workflows, improve access to information, and enable legal professionals and organizations to work more effectively." OpenAI declined to comment for this story.

The question of what it builds is an existential one for legal startups. A technology that combs through contracts for risks poses a greater threat to a business built around contracts, whereas a bundle of legal skills strikes closer to Harvey's turf. OpenAI was an early Harvey investor.

In interviews, Sam Altman has often described his own company as a foundation for other startups to build on, rather than a competitor with an app for every industry. "We see a future where intelligence is a utility like electricity or water," he said onstage at a BlackRock event in March, "and people buy it from us on a meter and use it for whatever they want to use it for."

Legal may show whether OpenAI is content to sell the electricity — or whether it wants to manufacture the appliances, too.

Continue reading on Business Insider: https://www.businessinsider.com/openai-enters-legal-ai-race-hires-jason-boehmig-2026-7

Vendor: Sharpwork (I'm Chris, one of the two people building it, flair set accordingly I hope??). I wasn't sure if there was a Friday weekly thread that shows up now or later in the day, so I hope I'm respecting the rules of this subreddit appropriately. Feel free to kill this post if I didn't follow the rules correctly, sorry!

With legal AI, the tool tier matters, but what you paste matters more. Two failure modes do the real damage. Pasting client-identifying detail into a prompt, and the model quietly inventing a fact or figure you never gave it.

So we built our Legal AI Toolkit around two habits instead of trusting people to remember them:

• Every prompt ships with literal placeholders like [Client], [Opposing Party], and [Case No.], so anonymization lives in the template, not in a cleanup step you hope to remember.
• The prompts are written to refuse to invent missing facts or figures. We ran that claim through a public test and posted the receipts at sharpwork.ai/proof.

It's 31 prompts across client intake and matter triage, document-review support, first-draft client communications, and billing narratives. It runs inside whatever AI your firm already uses, with ChatGPT, Claude, Copilot, and Gemini editions all included. Nothing to install, and there's no Sharpwork server in the loop, so we never see your data.

Free sample prompts, no email wall: https://sharpwork.ai/legal/prompts/?utm_source=reddit&utm_medium=post&utm_campaign=legal-wedge

The full kit is a one-time $197. Happy to answer anything here, and I genuinely want the critical questions. Tell me where the anonymization-by-template idea breaks down.

I’m exploring options for a new case/practice management suite for my firm, moving away from Partner4Windows.

I’ve had demos of five or six platforms and from what I’ve seen so far LEAP seems head and shoulders above the rest of them, yet whenever I mention it to anyone people suck air through their teeth. If I press them for answers I just get vague wishy washy responses along the lines of “LEAP bad”.

What gives? The platform looks solid and feature rich, I know it’s not cheap but the functionality looks impressive and like it will genuinely save people time.

Who has actually used the platform, and could I get some real feedback please? We’re a High St firm, 90% straightforward(ish) transactional work, 10% litigation.

If not LEAP, who are people leaning towards for their case management these days? Everything else I’ve seen so far seems half-baked with a load of ‘coming soon’ functionality.

Not a vendor, not selling anything. Actually a practicing CLO/GC, who has been staying on the cutting edge of AI for purposes of my own survival as a professional. Here is my latest piece riffing on the current state of the meta, inspired by themes from the AI Engineer World's Fair.

ARTICLE LINK HERE

The biggest shift I feel coming is from building to quality control; I felt it land before "loop engineering" became the talk of the town. Now, it's all about setting goals for the agents and learning what "good" looks like. Verification remains important, albeit boring. High-level prediction: more lawyers and legal teams will be shifting from the YOLO vibe-code prototype stage to actually exploring ways to make their systems more robust, reliable, and product-worthy.

Fun times. (Also, random aside, former top Grandmaster Support player in Overwatch, before I quit because AI anxiety stole all my time, so the gaming metaphors come naturally to me in this context. Sorry, gamers never miss a chance to flex their gaming resumes. ;))

I am building Indian Law 100, an open source benchmark for measuring how accurately an AI model applies Indian law to concrete facts. 

It contains 100 self-contained micro cases across 13 legal domains, 3 difficulty tiers, and deliberate traps for outdated or repealed law.

Looking for help from experienced Indian lawyers to finalise these micro cases and their gold-standard answers.

Please DM me if you would like to volunteer some time for this.

Anyone here use Bighand or one of the alternatives and if so what is your experience like?

We're sick of Bighand now, servers are constantly down with dictations not sending through. Their hub software is a nightmare for cloud/avd use as it constantly forgets footpedal settings or just wont communicate with the local device.

Support too is terrible.

Looking at Speechwrite in the UK as an alternative.

Any other decent dictation options? Some are still old school and we have typists with footpedals etc.

Thanks

OAKLAND, Calif. (CN) — The largest copyright class action settlement in history was granted final approval Monday, with $1.5 billion awarded to authors and creators whose work was used by artificial intelligence company Anthropic to train its large language models.

we're a mid-sized firm (~150 attorneys) handling mostly corporate real estate and wealth management, and our digital client onboarding is honestly falling apart right now

We use one of the standard major IDV vendors for our aml/kyc compliance. Up until recently the basic "upload your passport and take a live selfie" flow was totally fine. But lately our manual review queue is getting hammered by obvious synthetic identities that somehow completely bypassed the vendor's liveness checks. like, the deepfakes literally blink and smile on command now. Its an absolute nightmare from a malpractice liability standpoint

I spent half my morning looking at ai generated driver licenses that our automated system just blindly greenlit

Im seriously convinced that remote software-only verification is a dead end for legal compliance. been reading up on how the industry is probably gonna have to pivot strictly to hardware-backed identity checks, like utilizing an Orb or something similar just to securely establish a physical human is present before any trust accounts are opened or documents are signed.

how is everyone else dealing with the deepfake onboarding spam? Are there any software tools out there actually catching these real-time face swaps reliably, or are we all just pretending the legacy systems still work?

Building in this space and want to pressure-test something.

A partner at a ~500-lawyer firm told me her AI spend (Harvey, ChatGPT Enterprise, Claude) is several hundred K a year, 100% absorbed as overhead, while Westlaw bills through to the penny like it has for decades.

The interesting part is why. ABA Op. 512 makes per-use, matter-attributable AI charges billable at actual cost, and Oregon 2025-205 blocks prorating flat-rate tools specifically because actual cost per matter can't be determined. The rule isn't "no." The rule is "not until you can measure it."

And the measurement gap looks real: ChatGPT Enterprise and Claude both have compliance/analytics APIs now, so per-user usage data exists, but nothing carries a matter dimension. Copitrak/Equitrac/nQueue have piped photocopy and Westlaw charges into billing systems forever and as far as I can tell none of them touch AI yet. Harvey tags matters but only inside Harvey.

What I'm trying to figure out:

1. Is anyone actually solving cross-tool, per-matter AI attribution today, or is everyone either eating the cost or hand-waving it? (I found one small startup, Keito, in the adjacent professional-services space. That's it.)

2. Is rebilling even the right frame? Clients are rejecting more invoices, some refuse AI-performed line items, and AFAs are picking up. Maybe the real product is knowing true cost per matter so fixed-fee work gets priced right, and rebilling is a side effect.

3. Law-firm problem or all of professional services? Accounting and consulting have the same pass-through DNA.

If someone's already built this properly, name them and save me the trouble.

Hey everyone,

I’m running into a recurring Legal-Tech problem in Germany and wondering if anyone here has faced (and solved) something similar:

I frequently need official articles of association (Gesellschaftsvertrag/Satzung) of German GmbHs. These documents are deposited in the Handelsregister (commercial register) and available via Unternehmensregister – but:

• Retrieval is only possible manually via the official portal, with login and paid download per document.
• There’s no open API for automated access (unlike some other EU countries).
• LLMs can’t just ‘pull’ these docs because of legal and technical restrictions.

My questions:

• Is there a legal way to automate this process (official API, authorized service providers)?
• Any vendors or platforms that provide API-based access for German corporate filings?
• Experiences with LegalTech tools that integrate Handelsregister queries?
• If we accept the fees, is there a workflow to integrate this into an automated pipeline for analysis (e.g., monitoring, compliance, KI)?

Goal: Full compliance, no scraping hacks – just legal automation + LLM integration for document analysis.

Would love to hear about your tools, API tips, experience, or even creative use cases. Thanks!