r/legaltech

In legal onboarding, especially with paralegals and consultants, verification is becoming a constant challenge. Every firm seems to handle it differently, and a lot of it still depends on manual confirmation from licensing bodies.

It slows down onboarding even when everything else is ready to go. We recently had a candidate waiting almost two weeks just for verification clearance.

Who does everyone think wins? The first mover, fast follower and/or a third unknown company?

I’ve gotten very mixed feedback about it. About half the firms I work with do it, the other half don’t. Most of the ones who don’t feel it’s unethical.

Curious how the attorneys on this page feel about it.

Currently in the interview process with Legora for a GTM role based in Stockholm and trying to get a better sense of day-to-day culture.

For anyone who’s worked there (or closely with them), what are the working hours typically like? And how would you describe the culture in terms of pace, expectations, and work-life balance?

Seeing articles of 996 culture and daily dinners in the office aren't filling me with confidence....

Appreciate any honest insights!

Has anyone worked on the Revenue/Sales side for Consilio? How was your experience?

How is Consilio viewed in eDiscovery and Legal space? How do they compare to the Epiqs UnitedLexs and Big 4s of the world?

Any other insights are incredibly helpful

I've been able to try most legal "AI" services, but decided to do some tests with WL Advantage, which I haven't used.

It's absolutely horrible. No nuance to understanding filings. Suggests defenses and counterarguments that would fail in court because the counterarguments/defenses miss key facts that distinguish the cases I provided from the counterarguments/defenses. When I used the Claims Explorer, it pulled in claims that weren't applicable, and not a single claim that I had been able to find in my own research was there.

Building out my own databases using CC yields much better answers than WL, and in less than the 15-30 minutes it seems to take for WL AI to return an answer.

The only things WL and LN hold of any value are case law and secondary sources, but even that gate is being broken down as more free-access law databases become available.

I guess I expected it to have some "wow" factor, but not "wow, this sucks."

These companies have to see the writing on the wall that their value is sinking fast.

Keen to understand if big law are looking to request massive price discounts or alternatively abandon Legora/Harvey completely in light of Claude for Legal, which seems to offer 80% of features of what Legora/Harvey offer for a fraction of the price.

The Claude for legal news has been interesting, especially in legal research. Has anyone had a chance to check it out yet and start connecting? I connected Trellis and Midpage and it’s been really cool so far. I was able to search specific cases and have claude run some analysis on them and build me charts on top of the data that’s not as readily available otherwise. What connectors do you think actually deliver value and what do you hope to do with them?

This might be a bit long because i’m still thinking it through, but i’ll try to keep it tight.

i’ve been watching the Claude for Legal launch and wanted to sanity check my read here.

Everyone is understandably comparing it to Harvey, CoCounsel, Legora, Westlaw, etc. makes sense. that’s the obvious legaltech angle.

but i’m not sure the important part is “Claude is now for lawyers.”

Feels more like legal is just the latest vertical Anthropic is plugging into a bigger infrastructure strategy.

a week before the legal launch, they pushed a similar thing into finance. agents/templates/workflows for pitchbooks, audits, credit memos, financial analysis, all that kind of stuff.

Then small business. QuickBooks, PayPal, HubSpot, Canva, DocuSign, Google Workspace, Microsoft 365.

Now legal. Westlaw, CoCounsel, Harvey, DocuSign, Box, Everlaw, Microsoft 365, legal plugins, MCP connectors.

and at the same time you have Notion turning the workspace into a place where agents, data, workers and humans can operate together. Microsoft putting Copilot where work already happens. Salesforce pushing agents into the customer operating system.

So to me the pattern is less “AI company launches legal tool” and more “get the model closer to the actual workflow.”

the boring historical comparison in my head is Word.

Lawyers didn’t stay in Word because Word is beautiful. they stayed because the work lived there. drafts, comments, redlines, templates, partner edits, client versions, final_final_v7, all of it.

once the work lives somewhere, everything around the work adapts to that place.

That’s why i think people sometimes underestimate these connector/MCP moves. not because MCP-ready is magic. it’s not. but if models can call tools, pull context, trigger actions and sit inside the systems where the work already happens, then the model is only part of the story.

the real question becomes: who owns the workflow layer before the lawyer even sees the work?

For legal, that means Word, Outlook, DMS, CLM, DocuSign, intake, research, matter updates, e-discovery, billing, client systems, whatever people already live in.

and this is where i think the next vendor wave gets annoying.

A year ago everything was AI-powered. then everything was a copilot. then everything was an agent. now i think we’re going to get the same thing with Claude/MCP/connectors.

built on Claude. MCP-ready. agent-native. workflow orchestration. connects to every model. plugs into your existing tools.

Some of that will be legit. some of it will be reheated wrapper language.

the questions i’d ask are way more boring:

• what workflow does this actually improve?
• where does human review happen?
• what does the audit trail show?
• what system of record does it touch?
• what happens when it’s wrong?
• what breaks if the vendor disappears?
• does the connector actually change the workflow, or is it just a nicer entry point into the same product?

i’m not anti-vendor (maybe i am). some vendors are going to be very valuable here, especially if they own real workflow, review, implementation, auditability, or domain-specific data.

but i do think Claude-powered or MCP-ready is a bad starting point for buying anything.

better starting point is probably: what work are we trying to make easier, safer, faster, or more auditable?

then figure out if the answer is a vendor, an internal workflow, a connector, a model, or some boring mix of all of it.

am i overreading this?

are firms actually starting to think in terms of workflow ownership, or is the buying conversation still mostly “which AI tool should we get?”

btw i did a waaay longer version of this for the blue social media but waay too long for here, can share it in comments if wanted.

I spent some time working with lawyers, validating the workflows results and general UX getting the product to where it is today, it is directly available on GitHub for you to fork, self host or whatever have you.

I have spent my fair share in legal tech, meeting the founder of Legora, Max, on several occasions, other than being a charismatic leader, here are a few other things became clear to me:

- These companies are run by some of the best founders this generation has seen, their "Let's rule the market" attitude culturally is in every corner of the company.

- Launching these companies today wouldn't have reached where they are today, a lot of the conversation has reached "But Claude code can...". Especially with their own Legal Agents now.

- The sales and GTM engine these companies run on is a master class that should be studied, management books should be written on them.

- These products have priced themselves out of smaller firms, as the website shows, I have sorted out several comments from this subreddit, lawyers, paralegals and the lot. It is insane to me in some cases these products can cost well above $1k+/seat.

- Shepardizing is pricey, if it's with LexisNexus or Westlaw comes at a big premium, this knowledge is or should be free and available at masses. I have integrated with open sources to protect this across different jurisdictions and types of law.

Lastly, I am happy and amazed that the industry that was so underserved by tech is now the frontrunner.

EDIT:

1. As Plane-Coconut-4077 and others have pointed out, this work is forked from Mikeoss, integrated with LegalDataHunter, and validated 25+ workflows.

2. I was not aware of the correct usages of various licenses, this is now rectified on Github and the website. Apologies for sending the wrong signal here, this was not the intention at all

I'm setting up an API deprecation policy for a B2B SaaS company (~500 employees, 1,000+ customers across the EU and US, many with deep API integrations). I need to decide where the deprecation commitment should live contractually.

Our legal team's position is to keep it in the Terms and Conditions rather than surface it in enterprise contracts, primarily to avoid friction in sales conversations with prospects. My concern is that this leaves us without negotiated customer consent to our deprecation rights - so when we eventually need to retire a version a major account depends on, we'd be relying on a clickwrap term the customers may argue was never part of the deal.

I want to propose incorporate the deprecation policy (notice periods, sunset mechanism, migration windows, etc) on it on the enterprise contract itself (MSA - Master Service Agreement), but not sure how much I can/should push.

How do mature business es actually structure this? What approach is the right way to balance sales friction against enforceability?

Ps. I'm coming from a Engineering background. So I'm a bit outside of my legue here.

at a convention last week, I was talking to a vendor about their AI product, and I was appalled by the sales rep.

not on a personal level, but in the total lack of understanding of what the product could do for me. I kept trying to ask, in many different ways, what the AI tool does, and not a single answer made me want to even demo the tool.

if it’s something I can already do easily, why do I need your product?

if it’s something I can do with automation, why do I need an AI tool?

if it’s something that’s already built into a basic function of existing and widely used software, why would I use your tool?

the sales rep was not a tech person, was not a lawyer, and was of no use whatsoever. I went in open minded and walked out thinking that product can’t do anything better than a tech stack from 2010.

nobody is buying your product because its interesting or well-made. the only reason to buy your product is because it can do something that will make or save money. if you can’t articulate to the client how your product will do that, and do that better than what they already have, you're just wasting their time - and they’ll never give you that again.

Has anyone who is using or used Harvey compared the results for legal research, drafting, summarization to just regular latest claude or chatgpt models and knows the different? Obviously Harvey has a layer of personas in front but curious to see how drastic the differences are and what people are actually using Harvey for at corporations.

I think the project has now reached the point where the real question is no longer:

“Can AI reconstruct a messy file?”

It is:

“Can the reconstruction survive hostile edge cases?”

Because the dangerous failures are not usually obvious hallucinations anymore.

They are procedural distortions that still produce perfectly reasonable-looking summaries.

A few of the edge cases we are now stress-testing against:

- conflicting timestamps across systems
- forwarded emails that subtly change evidentiary meaning
- duplicate-looking records that are procedurally distinct
- downstream documents inheriting unresolved assumptions
- summaries that quietly convert uncertainty into settled fact
- contradictory narratives that are both internally coherent
- missing participants later restored into chronology
- records that only become contradictory after awareness timing is reconstructed

The interesting part is that many of these files still generate “clean” outputs.

The distortion only becomes visible once chronology and procedural context are restored.

That has shifted the testing focus away from:
“Did the AI summarize the file correctly?”

and toward:
“Did the reconstruction preserve the uncertainty structure of the file?”

At this point, the hardest problems are no longer document problems.

They are procedural-state problems.

Meaning:
- when did an assumption start propagating?
- when did uncertainty stop being treated as uncertainty?
- when did later records begin inheriting disputed context as if it were settled fact?

That is where a lot of the reconstruction logic either survives or breaks.

For people here who deal with messy litigation, investigations, compliance reviews, or chronology-heavy disputes:

What are the nastiest reconstruction failure modes you have personally encountered?

Not legal theory.

The actual procedural edge cases that turn a file into a reconstruction sinkhole.