Product update · August 2026

What's new in ArsLex

A large wave of Discovery Suite work shipped this month, along with two changes to how we hold your firm's data. This note is written for the people doing the review, not for the people who build it.

Some items below are switched on per firm. If you do not see one in your account, ask us and we will turn it on.

Review

Faster, and harder to get wrong.

Bulk coding, with a preview you can check first

You can now code an entire search result in one action. Nothing is written until you have seen the preview, which tells you how many documents actually change as opposed to already carrying that call, which family members come along with them, which families would end up split with a parent produced and a child withheld, and, most usefully, every document where the AI's read of the record disagrees with the call you are about to apply. That last list is advisory. It never blocks you and the lawyer always wins. If the gesture turns out to be wrong anyway, one action reverses it, and anything a colleague edited in the meantime is left alone rather than stamped over. Two things stay out of bulk on purpose: removing a privilege mark is a one document decision, because over-withholding shows up on a log and under-withholding is a waiver.

Read the emails that carry the conversation

ArsLex now works out which messages in a thread actually carry content and which are fully quoted inside a later reply. You review the ones that carry the conversation, and the rest of the thread follows your decision with a record of where that decision came from, rather than being quietly filled in. Attachments stay with their parent email throughout, including inside one continuous Bates range.

Batches carved by topic

Instead of handing a reviewer the next thousand documents in whatever order they arrived, you can carve the unreviewed remainder into batches by subject, largest group first, with anything that did not group cleanly kept in its own batch at the end. A reviewer who stays inside one subject for an afternoon codes it more consistently than one who bounces between six.

Quality control sampling that can be reproduced

Sample a completed batch for a second look. The draw can be uniform, or weighted toward the disagreements that carry real risk, meaning the documents where the AI called something responsive, hot, or high exposure and a human coded it out. Either way the report states in plain words which method drew the sample and what the resulting rates do and do not describe, because a weighted sample presented as a random one is a false statement to a court. Published seeds reproduce the same draw on someone else's machine.

A better AI first pass on long documents

Previously, a document too long to read in full contributed its first sixty thousand characters, so a three hundred page export whose material paragraph sat on page 180 was reviewed on its cover sheets. The pass now selects the passages that actually bear on your criteria, assembles them in the document's own order rather than in relevance order, and states on the record which pages it read, how much of the document that covered, and that the pages were not sequential.

Search by concept, and a production grouped by subject

Alongside keyword and phrase search, you can now search by concept and find documents about a subject even when they never use your words for it. The same machinery groups a production into subject clusters, with a quality panel that surfaces the documents fitting nowhere, which is frequently where a failed scan is hiding.

Production

And defending it later.

How we hold your data

Zero-retention AI, encrypted custody, provable deletion.

Nothing here changes the headline, which has never moved: your content is never used to train any AI model and is never retained by any model provider. What changed is the custody side.

Questions

Want a walkthrough on your own matter?

We are glad to walk your team through the bulk coding preview or a quality control sampling report against a live matter. Write to admin@arslex.ai.