By Andrew Milauskas, Chief Operating Officer, Page One
I have spent roughly 15 years working in Relativity.
Over that time, I have watched the platform and the legal technology industry around it change dramatically.
We went from managing increasingly large document populations, to sophisticated analytics, technology-assisted review, cloud-based workflows, and increasingly intelligent tools for organizing and understanding evidence.
Each of those changes mattered.
But ClaiR feels different.
It feels less like another feature being added to the legal technology stack and more like the beginning of a new way of interacting with legal data with the power of RelativityOne.
For years, experienced Relativity users have developed a particular way of thinking about information. We build searches. We create fields. We structure review workflows. We use analytics. We filter, categorize, sample, validate and refine.
Those skills are not going away.
But AI changes the interface between the professional and the data.
Instead of only asking, “How do I find these documents?” we can begin asking, “What does this evidence tell me?”
From Searching Data to Interrogating It
Traditional eDiscovery workflows are exceptionally good at helping legal teams locate information.
Give an experienced professional a large data set and the right tools, and that person can methodically narrow millions of documents into the information that matters.
But the process still requires the human being to design much of the path.
You need to know what searches to run, what concepts to explore, which custodians matter, which dates are significant and which documents deserve attention.
Generative AI introduces another layer.
Now we can begin interacting with large collections of legal data conversationally and analytically.
A lawyer or investigator may be able to ask questions such as:
What happened during the three weeks leading up to this event?
Who appears to have known about this issue?
Where do the accounts of these two individuals conflict?
What documents support or contradict this theory?
What themes appear repeatedly across this data set?
Those are not simply document-retrieval questions.
They are investigative questions.
And that is why I believe tools like ClaiR have the potential to change how legal professionals think about the platform itself.
The Interface Is Changing
For much of software history, users have had to learn the language of the software.
We learned menus. We learned search syntax. We learned fields, filters, operators and workflows. The better you understood the system, the more powerful you became.
AI begins to reverse that relationship.
Increasingly, the software can begin to understand the language of the user.
That does not eliminate the need for expertise. In legal technology, I would argue it makes expertise even more important.
A sophisticated user still needs to understand the underlying data.
What was collected?
What was excluded?
What metadata exists?
What does the system actually have access to?
Are the documents complete?
Are there privilege concerns?
Is the AI making a conclusion supported by the evidence, or simply presenting a plausible interpretation?
The ability to ask a question does not guarantee the quality of the answer.
That is where experienced professionals become critical.
AI Does Not Eliminate Platform Expertise
There is a temptation whenever a new technology arrives to assume that it will replace the skills that came before it.
I do not see that happening here.
The best ClaiR users will likely be people who understand both the technology and the underlying legal process.
They will understand data structures. They will understand discovery. They will understand investigations. They will understand how attorneys actually build cases. And they will understand how to test and validate AI-generated analysis.
In other words, AI does not reduce the value of expertise.
It amplifies it.
A novice may be able to ask an AI system a question.
An expert knows whether it was the right question, whether the system had the right information to answer it, and whether the response can actually be trusted.
That distinction will matter enormously.
The Workflow Will Change
The most exciting possibilities may come from workflows we have not fully designed yet.
Imagine early case assessment where a legal team can rapidly interrogate a large collection of communications and begin developing an understanding of the matter in hours rather than days.
Imagine an investigation where attorneys can identify potential contradictions, relationships and timelines before traditional review begins.
Imagine preparing for a deposition by asking the system to surface communications involving a witness, organize relevant events chronologically and identify documents that contradict prior statements.
Imagine receiving a new data set and being able to explore it immediately rather than waiting until every traditional review workflow has been fully constructed.
None of those scenarios eliminates document review.
They change what happens before, during and after review.
That may ultimately be the bigger transformation.
A New Kind of Relativity Professional
Over the next several years, I believe we will see a new category of highly valuable legal technology professional emerge.
These people will combine traditional eDiscovery expertise with AI fluency.
They will understand how legal data is structured.
They will understand how to interact with AI systems effectively.
They will know how to validate answers.
And perhaps most importantly, they will know how to translate legal questions into analytical workflows that combine humans, technology and evidence.
That is a very different skill set from simply knowing which buttons to push in a software platform.
It requires curiosity.
It requires legal process knowledge.
It requires technical judgment.
And it requires a healthy amount of skepticism.
The Beginning, Not the Destination
Whenever a significant new technology appears, the first version is rarely the final story.
The most important developments come later, when users begin discovering workflows the original designers may not have anticipated.
That is what makes this moment interesting.
ClaiR is entering an ecosystem where enormous amounts of legal data are already being organized, reviewed and analyzed.
Connecting modern AI capabilities directly to that environment creates possibilities that are difficult to fully predict today.
After 15 years working in Relativity, I have seen plenty of technology described as transformative.
Some of it was. Some of it was not.
But the shift from searching legal data to actually interacting with it through AI feels meaningful.
We are still going to search. We are still going to review. We are still going to validate.
But increasingly, we are also going to ask questions.
And the platforms that can help legal professionals turn those questions into reliable insight may define the next era of legal technology.