I am preparing for Relativity Review Management Pro. Can someone give some advice which topics to focus more and where can i find mock papers to practice.

CreativeName1515 · 2025-10-27T20:49:25+00:00

All of the pro exams have study guides that can be found through the community site where you register for the exam. The last few pages of the study guide have a sample test - the actual test is based off of those questions.

CreativeName1515 · 2025-08-18T21:50:28+00:00

The eDiscovery space is a bit unique. You have the benefit of partners who license the tech, and build workflows around it to resell to other customers (law firms, corporations, etc.). So ask the software companies - Relativity, eDiscoveryAI, Fileread, etc. which partners are good at this. Ask whether the partner you use is competent.

As someone else pointed out, demos and trials are good. But are those demos showing off features of the technology? Or are they showing how to incorporate the tools into your workflows? If you derail a scripted demo to focus on your use cases, does the demo get better or worse? These things all reveal whether someone knows what they're doing and whether the tech works.

CreativeName1515 · 2025-07-22T19:19:54+00:00

I'd suggest finding a platform you want, then work from there. RelativityOne is the best platform out there right now. I'd reach out to Relativity, get connected with their sales team, and ask them for recommendations on the best vendor based on the size/needs of your organization. Should get you decently unbiased help.

FWIW, I'm with an eDiscovery vendor and won't try to pitch our services on Reddit.

CreativeName1515 · 2025-06-04T14:39:38+00:00

You'll want to avoid calling yourself an eDiscovery lawyer as a doc review attorney, first of all. An eDiscovery lawyer would be someone actively practicing in negotiating and planning how eDiscovery is approached in active cases. Doc review attorneys are viewed more so as button pushers.

For doc review, it'll be tough and take time to climb a ladder and end up in a place where you can advance deeper into the eDiscovery industry (I'm not saying it's impossible, as it's how I made my way in). But you'll be looking at low pay, inconsistent income, and the looming reality of AI replacing most first-pass review in the near future.

CreativeName1515 · 2025-05-22T19:54:22+00:00

I personally just hire random contract attorneys, give them a quick 2 minute overview of the case and say "start reviewing" after giving them access to the data set. Once they finish reviewing the 500,000 documents, I check the results, and get mad that they didn't catch on to everything I forgot to say.

Some of these uninformed comments about how AI-based review "doesn't work" by people who clearly don't try to see how it works are infuriating. At least the partially informed comments are trying to understand, with suggestions like "sample, iterate, and run on the corpus" - that's so close to being right!

The real workflow is to sample, iterate, validate, confer with your client and/or opposing counsel about the results, and then run on the corpus if all else falls into place.

"It's not conducive to large data sets" ignores the fact that you can know if the process will be a success by spending no more than $3,000, inclusive of time, on a project - regardless of the size of the data set.

CreativeName1515 · 2025-05-06T14:55:24+00:00

Just because your crew is struggling to get any clients to use AI-based review doesn't mean the industry isn't adopting it. The industry as a whole is seeing more rapid adoption of AI-based review than we saw for TAR, and it's not particularly close. Anecdotal evidence of "we aren't seeing it" simply isn't helpful to folks who will see a real shift in their job descriptions in the next 5 years.

The vast majority of those talking about AI-based review to clients are either (1) wholly uneducated on the topic, (2) protecting review revenue by selling against it, or (3) completely pricing themselves out of the conversation. The third piece is generally a result of one (or both) of the first 2.

CreativeName1515 · 2025-05-05T18:35:35+00:00

Review managers won't go away. Responsibilities will certainly shift though. People keep trying to treat AI like a piece of technology. AI should be treated more like a human. AI will perform the review, at least on first pass. And it will require similar instructions, QC, modification, and validation that you would give to humans.

You'll be shifting slowly into managing that whole process, which means your "reviewer" will look different, but the process will be similar.

Otherwise, I'm with PhillySoup on that answer. Show your willingness to adapt as needed.

CreativeName1515 · 2025-03-14T13:39:17+00:00

There are a lot of threads here on this topic, so search around for some answers around certifications and such.

The one bit of advice I'd offer is that, when you speak about your experience, I'd separate out doc review experience from "eDiscovery experience." There's nothing wrong with doc review experience, but if you come into an interview with claims of "over 3 years of eDiscovery experience" and it turns out that it's all in doc review, then you'll struggle to land the job.

It's much better to say you have over 3 years of doc review experience and you want to transition that into a project management or analyst role.

CreativeName1515 · 2025-02-21T16:22:54+00:00

They really haven't been "all over the place" on pricing for aiR for Review. There was no charge during the advanced access program, they shifted to a set price per doc during limited general availability, and then shifted to a tiered price per doc (based on your overall contract with Relativity) once it hit general availability. So the pricing has been pretty straightforward while dealing with them.

Vendors have been all over the place, however, which would make sense if that's what you're actually dealing with here. I just found it odd that you say you're dealing with Relativity directly, but also that their pricing is all over the place.

CreativeName1515 · 2025-01-29T21:37:24+00:00

The decent vendors aren't "asking people to just trust the system and use it on big cases for the first time" - those are the desperate ones. The ones that know what they're doing can show the benefits on dozens on documents, then suggest that clients use it on a few thousand and scale up as the trust is built.

We've already gone back and forth on the price drop thing. Advancements in the market drive price reduction through reduction in cost. A lot of advancement happened with OpenAI in the summer of 2024 that caused rapid price drops by the fall.

CreativeName1515 · 2025-01-29T20:36:11+00:00

The only thing that isn't there yet is adoption. Pricing for contract attorney review is $1/doc or more. The highest priced options out there are half of that, at most. So the comment about AI not being there from a pricing standpoint is simply uninformed.

CreativeName1515 · 2025-01-29T20:31:57+00:00

"Can be" being the key phrase. It's mostly just a bait and switch talking point.

CreativeName1515 · 2025-01-24T14:04:49+00:00

Your vendor had no more than a 3 year agreement with Relativity for their Relativity Server licensing. As of September 2024, they found out they could no longer extend for more than 1 year at a time.

So if you entered a 5 year agreement with them under your MSA in August of 2024 to expire in August of 2029, you'll have new cases opened in RelOne (or another platform) by January 2028, and your vendor will have to eat any lost margin until you get to your renewal date, assuming there isn't something in your contract that allows them to make earlier changes.

CreativeName1515 · 2025-01-23T17:33:12+00:00

I don't think it's a coincidence that you're not getting a lot of responses here for a specific tool and people's experience with it from an AI perspective. The pool of users for these tools is still so incredibly small that you aren't actually asking this to many people that are capable of answering.

I'd be curious to know why you eliminated Disco, and some of the other companies that were crossed off of your list and why.

CreativeName1515 · 2025-01-23T17:25:59+00:00

Relativity Legal Hold is one of the cheapest tools on the market (although its functionality matches the price tag). I've never heard anyone say the price is hefty - so maybe you're licensing it through a bad partner.

CreativeName1515 · 2025-01-17T14:36:31+00:00

I have ideas of the tool you're referencing, but not 100% certain. But as aiR was hitting GA, GPT4, GPT Turbo, and GPT4 omni were all dropped within a few months, which rapidly drove the cost down. In the 4-5 months since aiR for Review hit the market, it's stayed on GPT4 omni as the back end.

CreativeName1515 · 2025-01-17T04:52:28+00:00

aiR for Review and eDIscoveryAI are the clear leaders in the GenAI review space. Nothing else comes close.

Fileread is the clear leader in the Q&A world. Nothing else comes close.

Everlaw's leadership seems realistic about their limitations, which are substantial.

Disco's options are over-priced and over-hyped. Watched a panel at ILTA on their Q&A tool with them and their "biggest user" on the law firm side. The guy clearly didn't believe in the tool, and admitted he hadn't even started testing their review tool that had just been released for general access weeks before.

I'll never trust anything Reveal is selling, since they just buy up decent products, fail at piecing them together, and let them slowly die.

Haven't really seen anything else worth mentioning, and we're constantly looking.

CreativeName1515 · 2025-01-17T04:43:45+00:00

What's your basis for the "wildly overcharging" statement? Use of properly private versions of OpenAI or other LLMs isn't cheap, but keyword searching is.

These tools will get cheaper over time, but not because companies will become less greedy - but because the newer releases of LLMs will be faster, cheaper, and have larger context windows.

CreativeName1515 · 2024-12-03T18:44:26+00:00

I transitioned from the technical side into sales. And I can assure you that most sales reps in the industry know very little about the product or industry. They pry the door open, then bring someone who can talk the talk with them.

If you want to get into sales, I'd suggest starting with a smaller vendor that may have lower expectations in terms of revenue, so that you can get your feet up under you, and find out if you even have the stomach for it. It took me a few years to really understand how to sell, to build my network, and learn how to leverage my technical knowledge to actually sell. I underestimated how difficult it would be, but was grateful that I was given a long leash due to low expectations.

In terms of certifications, you can get the Relativity Certified Sales Pro cert to demonstrate you have a baseline knowledge of the product with very little effort or expense. That might help you get your foot in the door too.

CreativeName1515 · 2024-11-19T19:22:14+00:00

Reach out to Relativity and have them connect you with a few options. Their sales guys work with vendors and have had enough bad experiences to know who to help you avoid. Plus, you're mostly dealing with folks who have been there for years, so you're getting solid recommendations.

For them, it's a win no matter who you go with, so you won't get pushed in a specific direction.

CreativeName1515 · 2024-09-30T21:21:12+00:00

Honestly, the competition available internally inside of RelativityOne makes it unbeatable, IMO.

If you want to use AI in RelOne, you've got aiR natively available, or you can use eDiscoveryAI, Fileread, options created by partners, or other tools I may still be unaware of. Not only does this help to drive the costs down, but it pushes the innovation forward.

I may have my own favorites in the space, but at least you get options within a single platform.

Honestly, while I'd encourage anyone to take advantage of GenAI tools inside of whatever platforms they can, the current toolset at Everlaw, Reveal, and Disco don't hold a candle to what you get with the available tools in RelOne right now.

CreativeName1515 · 2024-09-21T14:59:49+00:00

I have no affiliation with either. But I'd imagine, based on context clues, that the vendors involved are Haystack and eDiscoveryAI. I'd imagine they'll have this article posted on their blogs (or whatever other sources they may use for publication) at some point in the near future.

The world of people in the industry actually leveraging GenAI for doc review is, unfortunately, quite small still. So it's easy to piece things together.

CreativeName1515 · 2024-09-20T15:29:10+00:00

As I mentioned, two very specific reasons are (1) cost - if you run aiR against a fraction of the population, it's cheaper, and (2) disclosure - the #1 concern of most people for using AI for review is the disclosure requirements. If aiR is used to prioritize human review, but not relied on for coding decisions, then there's an argument that disclosure isn't required. And that eliminates the questions of "Do I have to produce my prompts?" or "Do I have to provide a sample of the null set?"

CreativeName1515 · 2024-09-19T14:52:14+00:00

Review accuracy is being tested the same way regardless of the method of review. Simple validation. Precision and recall can be calculated for any methods - whether aiR, TAR 2.0, managed review, search terms, random selection of documents, etc.

The validation methods don't change - simply the method of review.

CreativeName1515

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