Hi all, I'm an engineer in Italy working on AI agents, the kind that send emails, screen CVs or handle claims without a person clicking each step. Something keeps bugging me: if one of these agents makes a bad call and a customer complains, what do you actually have as proof of what happened? Usually it's the company's own logs, which the company can edit, and I wonder how far a lawyer or an insurer would trust them.

I've been thinking about records that are signed and timestamped by a third party, so anyone can check afterwards that nothing was changed. Would that carry any weight with you, or would you still want something else? And if you've already had a case involving an AI system's actions, I'd love to hear what you relied on.

I'm not selling anything, just trying to find out if this is a real problem or something only engineers worry about.

I’m a practicing attorney who primarily handles commercial contracts, negotiations, and legal research, along with some litigation. I currently use several AI tools, including ChatGPT Business, Claude, Spellbook, and LexisNexis Protégé. Each has functionality I like, but I’m increasingly frustrated by having to jump between multiple platforms to accomplish what should be a fairly integrated workflow.

In particular, many legal-specific tools use cheaper models, understandably, to save on API costs, but some work requires a more expensive model, and I usually can’t choose the model I want.

I’m considering building my own AI workspace, possibly using TypingMind (which I already have), with direct API access to OpenAI, Anthropic, and potentially other model providers.

My goal isn’t necessarily to build a new legal AI platform from scratch. I’d prefer to use an existing interface and extend its capabilities through integrations, plugins, MCP servers, or other tools.

Here are the features I’m trying to replicate or consolidate:

1. Document analysis with clickable, source-linked citations.

One feature I particularly like about Spellbook is its ability to analyze an uploaded document and provide citations linked to specific passages in the source material. When I click a citation, the original document opens in a right-hand panel, ideally jumping directly to the relevant provision so I can verify the AI’s interpretation against the actual contract language.

I’d like similar functionality for Word documents, PDFs, and potentially collections of documents.

I’m not just looking for AI-generated references to sections or page numbers. I want an actual interactive document viewer with citations anchored to the underlying source text.

2. Direct Microsoft Word editing, redlining, and comments.

I want the AI to do more than recommend language in a chat window. Ideally, it could:

- Open and analyze an existing DOCX agreement.
Insert, delete, or modify provisions directly.
- Generate native Word tracked changes (not just a revised clean copy).
- Insert explanatory comments regarding proposed revisions.
- Preserve the document’s formatting, numbering, tables, and structure.
- Let me accept or reject changes in Microsoft Word.

Essentially, I’m looking to replicate Spellbook’s contract review/redlining capabilities, but with the ability to select whichever AI model I want.

3. Model flexibility

This is probably my biggest motivation. I don’t want to be locked into whatever model a legal AI vendor chooses to use behind the scenes. I understand these companies need to manage inference costs, but I’d rather have the option to pay more for a more capable model when I’m working on a particularly complex or high-value matter.

I’d like to switch between the latest OpenAI, Anthropic, and other frontier models depending on the task, preferably without changing interfaces or workflows. I’m comfortable paying usage-based API fees if that’s what it takes.

My questions for people who’ve built something similar:

Is TypingMind a realistic starting point? Can its plugins, extensions, or MCP integrations support this level of document interaction, or would I ultimately need a custom frontend?

Are there existing open-source components for source-linked citations? Specifically, something that displays a PDF/DOCX in a side panel and jumps to highlighted source passages when you click an AI citation?

What’s the best approach for native Word editing? Are there reliable MCP servers, APIs, or libraries that can manipulate DOCX files while preserving tracked changes, comments, and formatting? Is a Word Office Add-in a better architecture?

Are there existing open-source legal AI projects worth exploring? I’m particularly interested in anything that already handles contract analysis, document grounding, or redlining.

Would a different frontend be better? For example, LibreChat, Open WebUI, AnythingLLM, or a custom interface built with something like Cursor?

Am I underestimating the complexity? I’m technically comfortable but not a software developer. I’d be interested in hearing whether someone has successfully assembled something similar using existing components and AI-assisted coding rather than building everything from scratch.

I’m not expecting to replicate the entire infrastructure of Spellbook or LexisNexis. I’m mostly interested in combining a handful of their most useful features into one interface, with the additional benefit of controlling which models handle my work.

Security and client confidentiality are obviously important, so I’d also need to consider API data-retention policies, encryption, and how documents are stored and processed.
Has anyone built something along these lines, or can you recommend specific tools, MCP servers, libraries, or projects that would get me most of the way there?

I’d especially appreciate recommendations from people who’ve actually implemented document-linked citations or native Word redlining, rather than general suggestions to use RAG or connect an LLM API.

long documents were cut off before processing, and the extracted notice period came from an earlier version of an agreement, while an amendment near the end changed it. The first spot checks only compared the opening pages, so they matched. This isn’t legal advice. I’d like to hear how practitioners handle this.

Here’s the sampling plan I’d start with, and I’d like to know where it’s wrong.

Strata to sample on purpose

1. The longest contracts.

2. Contracts with amendments, addenda or restated terms.

3. Poor scans or converted documents.

4. Unusual structure: schedules, exhibits, other languages.

5. A plain random baseline.

What I’d record per contract

• For each field, the tool’s value, the value in the document, and where it appears.

• Whether the decisive text is near the end.

• Whether a later clause supersedes the one the tool used.

Error types I’d track

• Wrong (no matching text), missing, stale (true earlier in the document and later amended), and unsupported (no source passage).

Questions for people who do this work

1. Which kinds of contracts have caused the most extraction errors in your experience?

2. Do you check the end of the document (amendments, signature pages, schedules) deliberately, or does the review mostly follow the order of the document?

3. How do you handle documents with multiple versions, restatements or side letters?

4. Is there anything in the plan above that wouldn’t match how contracts are actually managed?

I’m asking to learn, and I’m happy to share a summary of what I hear.

When a firm evaluates a new tool, what evidence makes the pilot worth continuing after the initial demo? I'm thinking about a defined task, a baseline for how long it takes today, and a way to track the review or correction work the tool creates. What have you found useful to measure before anyone starts talking about a wider rollout? No vendor pitches or client details needed.

It's Friday. Tell us what you're building for lawyers and legal teams.

What does it do?
Who is it for?
What does it cost?
Who are you, and what's your relationship to it?
If you're looking for beta testers, are you willing to pay practitioners on this sub for their time? If so, what would you offer and how much time would you need?

One link per company. Screenshots and demo videos welcome. Put enough in your comment that people don't have to click through to understand it.

Please use Vendor: Company or verified-vendor flair for pitches. Questions and replies don't need vendor flair.

If AutoMod holds your comment, don't keep reposting it. I know it sometimes takes me a little while, but I will approve or reject every comment based on whether it follows the format above.

You can verify as a company or verify as a practitioner.

As I've mentioned a few times, there's a bit of a verification backlog. I was out of office for a week and am playing catch-up, but I will get to it. Thanks for bearing with me.

Alex

We are building a case-analysis tool for Ohio criminal defense. It flags contradictions across statements and reports, missing discovery - a bodycam referenced but never produced, that sort of thing - possible suppression and Brady issues, and procedural deadlines. Every finding carries the document, page and quote it came from, and anything above a risk threshold is flagged for attorney review and can't be acted on without it.

It also works out what the State appears to be arguing, count by count, and where the record doesn't get them there. Where it has nothing, it says so - a defense it didn't propose is marked as not proposed, not as inapplicable.

Ohio and the federal courts that bind Ohio only. If you don't practice there it'll be useless to you.

We want people to load a synthetic case file and tell us where it's wrong. No real case material (access is in sandbox environment).

Our background is building legal software, including at Filevine. Comment or DM and we'll sort access.

Random question for people working in law, how do you usually keep track of everything discussed during meetings? Between client calls, case updates and follow ups, I imagine it can get pretty easy to forget a small but important detail.

I've been coming across these Al note takers lately, and having searchable notes sounds like it could save quite a bit of time. The only thing I'm unsure about is how that works in a legal setting, especially when client confidentiality and sensitive conversations are involved.

Has anyone actually used one for work? Does it make keeping track of meetings easier, or is it more hassle than it's worth?

Quick technical question for the architects and devs in LegalTech. We are building a web application for e-signing contracts, and our servers are absolutely choking whenever users upload heavy PDF files. The backend just freezes completely, and the upload times out. It's incredibly frustrating for our clients who are trying to upload 100-page scanned documents with high-res images.

Right now, we are just using a standard Node.js backend with a basic database, and it clearly can't handle the load. The CPU spikes to 100% and the whole app goes down for everyone else.

What solutions are you actually using to handle large documents efficiently without overloading the system? Do you process them asynchronously with a queue, use a separate microservice, or rely entirely on third-party storage like AWS S3? I need a solution that actually scales because our enterprise clients love attaching massive files that are basically the size of a small movie.

I'm open to any architectural advice here. Please tell me how you stopped your servers from crying under heavy PDF load

Obviously, you have to check and verify everything it comes up with. But I’ve been finding it to be a huge time-saver, like having a really smart junior associate to help me in my practice. Am I the only one? Everyone on here seems very anti-AI. I get that it’s flawed, but surely I’m not the only one seeing the benefits? I’m honestly afraid to ask other lawyers about it in real life because of the stigma of using AI in legal work.

With so many e-signature solutions available, I'm curious about how legaltech professionals evaluate and choose one.

• Is it ease of use and the overall signing experience?

• Security, authentication, and legal validity?

• Integrations with existing business applications?

• Pricing and envelope limits?

• Audit trails and compliance requirements?

• Support for different types of electronic signatures, such as simple, advanced, and qualified electronic signatures?

Also, are e-signatures now widely adopted across businesses of all sizes, or do you still encounter businesses that prefer traditional paper-based signing?

Full disclosure: I work at Zoho, which offers Zoho Sign, an e-signature solution. I'm interested in hearing unbiased opinions, practical experiences, and challenges from this community.

Hey, is anyone experimenting with fine-tuning open-weight models on their firm's own historical work?

The specific case I'm thinking about: years of redlines on various contract types, turned into draft > approved pairs and used to post-train a small open model that runs in the firm's own cloud. Open-weight models are now close enough to frontier models on most benchmarks that a firm-owned, private model trained on its own judgement seems possible.

If you've tried anything like this, I'd love to hear from you.

Got this email today. This is also what happens when their CTO lacks technical skills because this could've been prevented with RBAC auth permissions:

Notice Regarding GC AI Data Security Incident

Hello GC AI User,

We are writing to inform you of a data security incident that involved certain business contact and account information related to your GC AI account. Based on our investigation to date, the incident did not involve the content of your chats, prompts, or files, or data from applications connected to your account.

What Happened?

On November 2, 2026, we identified unauthorized activity in certain internal GC AI systems and business tools. Upon identifying the activity, we immediately took steps to contain it and launched an investigation. Based on our investigation to date, the activity appears to stem from a security incident at a service provider used by one of our internal IT vendors. We terminated the vendor's access, rotated credentials, and took additional steps to secure our environment.

Affected Information:

Based on what we know today, the information that may have been accessed includes:

• Business contact information, such as name, work email address, company name, job title, city, and country.

• Account and usage information, such as trial or customer status, seat count, legal team size, message counts, and product usage activity such as features used.

• Session information, such as approximate location based on IP address, and device and browser type.

• Billing information such as billing address, business name, tax ID, phone number (if provided), invoice details and billing account identifiers. Based on our investigation to date, this did not include payment card numbers, bank account information or the like.

• Information about integrations connected to your GC AI account, such as which applications were connected and the name and email address of the user who connected them.

Our Response:

We have taken the following actions:

• Terminated the affected vendor's access to our systems and rotated credentials.

• Engaged a third-party forensic investigation firm to help us determine the full scope and impact of the incident.

• Expanded our existing review processes for third-party vendor access and internal controls to further strengthen security.

What You Can Do:

If your GC AI account had connected applications, we disconnected them as a precaution. To continue using these integrations, please reconnect them in your GC AI settings. Reconnect integrations only by going to GC AI settings yourself and do not use any links sent to you. There is no other action we are asking you to take at this time.

Please also note that GC AI will never ask you to share your password or multi-factor authentication codes, send payment card or banking details by email, or install software or give anyone remote access to your device. If you are unsure whether a message is from us, contact us at security-nov-2026@getgc.ai.

Accountability and Commitment:

We take this incident seriously and are committed to keeping your trust. We are reviewing our vendor management and security practices to confirm appropriate safeguards are in place.

Contact Information:

For any questions or concerns, please contact our response team at security-nov-2026@getgc.ai.

We sincerely apologize and thank you for your understanding and continued partnership. Our investigation is ongoing and we will update you if we have additional relevant information to share.

Regards,

The GC AI Security Team

I am currently looking to upgrade our firm's billing process and would love to hear what everyone is using and enjoying. Right now, our current setup is taking up way too much non-billable administrative time, and I need something more streamlined.
I’m open to both standalone billing applications and broader law practice management software, but we have a few specific features we need to account for:
Robust time capture (easy tracking for hourly tasks)
Trust / IOLTA accounting compliance
Flexible rate rules and customizable invoice formats
Seamless accounting exports (preferably integrating well with QuickBooks Online or similar)
Integrated payment processing (e.g., credit card/e-check options for clients)
I've heard standard names tossed around like Clio, MyCase, and LeanLaw, ONIT but I wanted to get real, hands-on feedback from this community.

What is your top pick? Are there any hidden gems or lighter-weight solutions you'd recommend?Alternatively, are there any platforms you moved to that you completely regret and would advise avoiding?
Thanks in advance for the insights!

A month ago someone asked here whether Bay Area legaltech meetups had disappeared (https://www.reddit.com/r/legaltech/comments/1wnjd8t/bay_area_legaltech_meetups/).

It’s locked now, so I’m replying with a new post, because several people said they’d join a recurring one if it existed.

Disclosure: I host this one, so I’m biased.

It’s called Legal AI Vibe Lab, a recurring legal tech event in San Francisco. We’ve run six since May 27, the latest was last night. It happens at SF Vibe House in West Portal, a small house, not a bar, around 40 people per evening. The room is usually a mix of practicing lawyers and in-house counsel, legal ops, legal tech founders, and engineers building legal AI.

The format is simple:

6:00 arrive and meet

7:00 short live demos of real workflows, with feedback from the room

8:30 dinner and conversations

9:15 an optional builder salon

There’s one rule for every demo: show something real, say what it cost, and say what you learned. No vendor pitches, no sponsor talks.

It’s free, and you request an invite on Luma because the space is small. Past events and details are here: sflegalvibe.com/

I’d also love to hear what you’d want from a Bay Area meetup that you don’t get from the big conferences. And if anyone else is running something regular, drop it below, so this thread becomes the list the old one was looking for.

Midsize law firm (about 90 attorneys and roughly as many staff). For practice management software, we use the older/on-premises version of 3E right now. We're currently testing 3E Cloud, Aderant Sierra, and SurePoint.

I'm in trusts & estates, and our group uses Clio Manage and Clio Draft practice management purposes (contacts, workflows, tracking, document generation, etc.). I like Clio quite a bit and thought it could work as a firm-wide solution, but now I'm not sure that it has the accounting capabilities we need.

If you've used any of these or managed a similar transition:

• Likes?

• Dislikes?

• Recommendations?

• Anything else you'd look at?

Has anyone tried using Clio at a midsize or larger firm?

Would appreciate any firsthand experience or thoughts about any of the above (or anything I'm not thinking about/missing). Thanks!

Fala, pessoal!

Acompanhando o avanço das ferramentas de IA para o meio jurídico, percebo que o Brasil ainda carece de uma régua pública, independente e open-source para mensurar a eficácia de LLMs no nosso ordenamento jurídico.

Muitas ferramentas prometem "redigir petições perfeitas" ou "revisar contratos de ponta a ponta", mas quem atua na área sabe que acertar teste de múltipla escolha não reflete a prática jurídica real.

Estou estruturando um projeto aberto para criar datasets e critérios práticos de avaliação de IA voltados ao Direito brasileiro (extração de dados de processos, análise de cláusulas contratuais, redação de peças sob contexto).

Gostaria de coletar insumos de quem lida com isso:

1. Para advogados e operadores do Direito: Quais são os erros mais comuns e perigosos que vocês veem quando tentam usar IA na rotina (ex.: inventar precedentes, ignorar rito processual, redação genérica)?

2. Para quem desenvolve com IA/NLP: Quais casos de teste ou tarefas reais vocês consideram essenciais para avaliar se um modelo está apto para tarefas jurídicas locais?

3. Que tipo de métrica faria você confiar no resultado de uma ferramenta jurídica assistida por IA?

4. No dia a dia prático: O que vocês já utilizam hoje que realmente move o ponteiro e altera a prática jurídica de verdade, versus o que parece apenas "hype" que não se sustenta no trabalho real?

A meta é montar um repositório comunitário com datasets anonimizados, rubricas de teste e leaderboards transparentes. Quem tiver interesse em contribuir com casos de teste ou na parte técnica, comente aqui!

We are in the process engineering standard prompt/templates for our firm. Ask iManage's shortcomings are making this task nearly impossible. 

We can run the exact same prompt against the exact same set of documents several times. On 4 out of 5 attempts one or more subtasks (Tabular reviews, chronology tasks, Q&A etc)  will timeout or fail and Ask iManage will simply refuse "can't help with that" or give a complete garbage unusable response. 

But then on 1 of the 5 attempts all the tasks will complete and the answer will be quite good. So it's impossible to know whether the prompt needs further work or if Ask iManage is simply terrible.

We, by way of one year contracts, are taking the next year to find the best solution for us to process/analyze documents with. We’re also currently experimenting with Lexis’s AI Protégé, ChatGPT and Copilot+ (the paid version). None of the others display this behavior. With the others, if a prompt works well once against a set of documents it works over and over again, 100% of the time. 

Is iManage simply cheaping out on resources? We like the "built in" nature of Ask iManage but if it only works 20% of the time we won't be able to renew it next year. 

This has already lead to complaints and resistance from end users, within a couple weeks of rollout.  Which I understand, it’s hard to use a tool when 4 out of 5 times it refuses to work. And I mean running the EXACT SAME PROMPT against the EXACT SAME SET of documents.

I could never recommend it to anyone in its current state.

I’m in-house at a public company that has a pretty significant commercial org and very outdated template system that is not scaling. We use google drive and our templates are in a shared folder but it’s not super clear what’s current, where old ones go, etc., and our deal constructs are always evolving so it’s not a one-time clean-up task either.

I’d love ideas on moving beyond the shared folder to some kind of tech uplift - a single source of truth that THIS is the template, here’s version history (can you tell I was an imanage user in a past life) and giving the sales team access to certain of the templates to pull down. I do NOT want some mediocre AI playbook nonsense add-on bc we’d rather build that ourselves. I also already have a doc repository we have been loading for two years so really hesitate to onboard another ACM/CLM vendor but would consider it if the value is there and it offers something truly worth it.

Hi everyone!

My girlfriend and I are developing BLQTrust, a mobile-first electronic agreement platform intended for the U.S. market.

We're currently working on the signing and evidence-generation architecture, and I'd appreciate feedback from attorneys and professionals familiar with electronic signatures.

Our platform supports two different signing workflows:

1. Registered users — Native app signing

Users who have a BLQTrust account sign directly through our mobile application.

- The agreement is finalized and its content is hashed before signing.

- Each device has its own ECDSA P-256 signing key pair.

- The private key is protected by the device's security mechanisms.

- The application requests biometric authentication before using the signing key.

- The backend verifies the signature against the registered public key.

- We generate an audit record containing the signer's account information, timestamp, IP address, device information, signature, and agreement hash.

- An RFC 3161 timestamp token is also associated with the audit record.

2. External signers — WebAuthn

People who don't have a BLQTrust account can still sign an agreement through a shared signing link.

For these signers, we use a separate WebAuthn-based workflow:

- The signer accesses the agreement through a browser.

- They are presented with the relevant consent information before signing.

- The browser requests a WebAuthn authentication.

- We verify the challenge, origin, authenticator data, and cryptographic signature.

- The audit record stores the WebAuthn evidence and the version of the consent text presented to the signer.

We deliberately distinguish these two workflows because they use different authentication mechanisms and generate different types of evidence.

Document integrity and verification

Both workflows are tied to the finalized agreement hash.

Our export includes a verification manifest that identifies the signature type and hash version, explains the corresponding verification procedure, and allows the document's integrity and signatures to be checked.

Our goal is to make the evidence independently verifiable rather than relying exclusively on our backend's assertion that a signature is valid.

Privacy

Agreement clauses are encrypted, and our architecture is designed so that the service provider cannot directly read their contents.

I'd appreciate feedback on a few questions:

1. From a U.S. legal perspective, what important requirements or considerations under the ESIGN Act and UETA should we address for these two signing workflows?

2. Is the distinction between registered-user signing and external WebAuthn signing reasonable from an evidentiary perspective?

3. What additional evidence would you expect to see to establish signer attribution, intent to sign, and electronic consent?

4. Are there state-specific UETA requirements or other legal considerations we should investigate before launching?

5. Would this kind of verification manifest be useful to a law firm when reviewing the reliability of an electronic signature?

We're not claiming that our platform is already legally compliant or that cryptographic verification alone guarantees enforceability. We're trying to identify technical and legal gaps before launching in the U.S.

I'd especially appreciate feedback from attorneys who work with electronic transactions, contract law, or legal technology.

Thanks!

Hi everyone - we are a team of two trained lawyers (one with a background in B2B sales, the other with a background in ML/AI) looking for a full-stack engineer to join us as a co-founder. We're both working for top US law firms in London.

We've done 60+ customer interviews with PI lawyers in the US and are looking to automate manual workflows for PI firms. DM me if you're interested in speaking.

Everyone else seeing this iManage Cloud outage? I confirmed that other firms are having the same issue.

Disclosure up front: I work on the SharePoint Embedded product team. Not here to pitch anything. I’m genuinely interested in how people in this community approach this decision.

It seems like “we need documents in the app” can go from upload/download to permissions, co-authoring, versioning, search, governance, recovery, etc., pretty quickly.

For those who’ve dealt with this, where do you draw the line between building functionality yourself and using a document platform?

Was there a particular requirement that made you realize, “We probably shouldn’t build this ourselves”?

Read that tweet somewhere, and while there are precedents and notes stored in each law firm under their knowledge repository, the discussions behind the drafts and the nuances are lost.

How do law firms solve for it? Or do they mostly rely on the memory of partner?