That is a wrap on RelFest Chicago 2026. Three days at the Hyatt Regency Chicago, roughly 2,000 members of the legal data community, and one theme came up in nearly every conversation our team had: AI is moving review faster than ever.
Here is what we brought home, and what we think it means for anyone responsible for mobile data in litigation, investigations, and compliance.
Has AI in review moved from pilot to production?
Yes. A year ago most of the conversations we had about AI in review were about whether to try it. This year the question had changed. Teams are running AI-assisted review on live matters, and the question they are now asking is how to defend it. What was the model given? What was excluded, and why? Can you explain the inputs to opposing counsel and to the court?
That shift matters because it pushes attention to the one place AI cannot help you: the data that went in.
Why does defensibility start upstream?
Again and again, conversations came back to the same point: can you explain where the data came from and why you collected it? Review tools do not create defensibility. They inherit it. If the collection behind a review set is documented, scoped to the matter, and authenticated, every downstream step is easier to explain. If it is not, no amount of review-stage rigor fixes that.
Is mobile data ready for AI-driven review?
Email and enterprise sources mostly are. Mobile data often is not. It sits across dozens of messaging apps on personal devices, mixed in with family photos, health data, and private conversations that have nothing to do with the matter. Getting it into a review platform in a usable, threaded, properly formatted state has traditionally required a chain of manual handoffs. That is the gap most teams at RelFest were still working around.
Why is proportionality not optional?
Imaging an entire phone and sorting it out later creates privacy exposure that no downstream tool can undo. Once over-collected data exists, it has to be stored, secured, reviewed, and eventually defended. Targeted collection removes that problem at the source. Collect what the matter requires, document the scope, and keep the rest of the custodian’s life out of the review set. Courts and custodians both expect it now.
What does the Innovation Award signal for the industry?
While we were in Chicago, the ModeOne Integration received the Best Innovation: Workflows award at the 2026 Relativity Innovation Awards. We are grateful to the Relativity community, the judging committee, and especially the customers whose feedback shaped the workflow from the start.
We read the result less as a statement about ModeOne and more as a signal about where the industry is heading. Winners in this category are chosen in part by community vote, which means practitioners are telling vendors what they want: fewer handoffs. Targeted mobile collections should move straight into Relativity aiR, processed and review-ready, with the chain of custody intact, rather than ending with another export, another ticket, and another wait. Mobile data is being treated as a first-class source that deserves the same connected workflow email has had for years.
What should legal teams take away from RelFest 2026?
Faster review only pays off when the collection feeding it is targeted, documented, and defensible. Speed at the review stage amplifies whatever came before it, good or bad. The teams that get the most from AI review will be the ones that fixed collection first.
Thank you to the Relativity team and to everyone who stopped to talk mobile with us in Chicago. If we did not get the chance to connect, let’s keep the conversation going, or book a demo to see how targeted collections flow into Relativity aiR.