Live demo | 2026.2 launch

Can your AI show where it got that?

How to scale AI on your documents when trust is the blocker. A live demo of what's new in the 2026.2 release, where every value stays linked to the page it came from.

  • Thursday, December 3, 2026
  • 2:00 PM ET / 11:00 AM PT
  • 45 min + live Q&A

With Anthony Vigliotti and Kunal Bargotra

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‍Wednesday, December 2, 2026, 2:00 PM ET. 45 minutes, plus live Q&A.Watch your inbox for a confirmation email with your join link. Can’t make it live? We’ll send you the recording.
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Sound familiar?

Your AI can read the documents. Nobody can show what it read.

You want AI to take on more of the work without adding people. Then someone asks where a number came from, and the only answer is "the model said so." That's where most AI projects stop.

  • 01

    The pilot that never shipped

    It worked in the demo. Then it sat in risk review for a quarter, because nobody could show what it did.

  • 02

    The double check

    The AI pulls the values. A person re-reads the source anyway, and the time you saved goes straight back into checking.

  • 03

    The question years later

    An auditor, a regulator or a customer asks where a figure came from. The document is somewhere. The link to the page is gone.

  • 04

    The output nobody signs

    It looks right. But the person accountable won't put their name to it without the source in front of them.

In life sciencesA value has to trace back to its source document, years after filing.
In manufacturingQuality and supplier records have to hold up in an audit or a customer complaint.
In energyCompliance and contract records have to answer the regulator when asked.

What changes

Where the checking goes today, and where it goes next

  • The AI hands back a value with no source

    Every value links to the file, page and version it came from

  • Someone re-reads the whole document to check the AI

    Reviewers go straight to the source page instead of re-reading the document

  • Corrections live in email threads and spreadsheets

    A reviewer corrects, a second person signs off, and every version is kept

  • Nobody can say who touched what

    A full history of who opened, changed, reviewed or downloaded each document, whether a person, an agent or a process

  • AI projects stall at risk review

    Agents never see or do more than the person using them, in your own cloud, with your own model

What you'll see live

A working demo, not a slide tour

Four parts, in the order a document actually moves: from arrival to a value someone can stand behind. Then open Q&A with the people who build it.

  1. Documents in, usable data out

    Everyday business documents, pulled from where they already live and turned into structured data your systems and AI tools can use.

  2. Why you can rely on it New in 2026.2

    Every extracted value stays linked to the page it came from, with a full history of who checked or changed it, and when. Reviewers correct, a second person signs off, and every version is kept.

  3. Why it stays under your control

    You decide where people review. Agents can never see or do more than the person using them. It runs in your own cloud, with your own model.

  4. Where the line sits

    Your people make the call and sign it. The agents do the reading and keep the record, so your team works from sourced files it can defend.

Bring the document your team trusts least to the Q&A. We'll also show where it goes after 2026.2 and ask what you'd want first.

Why it works

AI only multiplies your team when people can trust what it read

Most teams already know AI can read their documents. What stops them scaling it is that they can't see what it read, or where. So someone checks everything by hand, or the project never leaves risk review.

Document systems store the file. Models answer from it. Neither was there when the page was read, which is why neither can point back to it. Adlib does the reading itself, so the link between each value and its source page is captured at that moment, not pieced together later. And it stays with the data for as long as the decision has to stand.

  • Linked to the source page
  • Full review history
  • People decide

If a regulator or your own audit team asked your AI to show its work tomorrow, could it?

Who it's for

Built for the people who own the process, and the people who own the AI

  • Measured on audit readiness

    Process owners in life sciences

    Regulatory, quality and clinical operations teams who need every value traceable to the document it came from.

  • Measured on quality + compliance

    Process owners in manufacturing

    Quality, supplier and compliance teams who need records that hold up when an auditor or a customer asks.

  • Measured on regulatory response

    Process owners in energy

    Compliance, contracts and operations teams who need to show where a figure came from, on request.

  • Measured on getting to production

    AI and data leaders

    See how source linking, agent permissions and your own cloud and model get AI past risk review.

  • Customers and partners

    Already working with Adlib?

    See what's new in 2026.2 and what it means for the work you already run with us.

Your hosts

Hear it from the people who build it

Save your seat
  • Anthony Vigliotti

    Anthony Vigliotti

    Chief Product Officer, Adlib

    Anthony has spent 20+ years in business workflow and intelligent document processing, leading product and partner strategy at Xerox, NSi, Nuance and Kofax. His focus: turning unstructured content into reliable, compliant, AI-ready data for regulated industries.

    LinkedIn
  • Kunal Bargotra

    Kunal Bargotra

    Head of Value Engineering, Adlib

    Kunal is a product owner who builds products around real-world problems. He brings hands-on experience in stakeholder engagement, market research and go-to-market strategy, and joins Anthony to walk through the 2026.2 enhancements live.

    LinkedIn

Before you register

Questions we hear first

Is this a sales pitch?

No, it's a live product demo. You'll see the 2026.2 release working on everyday business documents, then ask the product team whatever you want.

Can't make it live?

Register anyway and we'll send you the recording.

Does the AI make the decision?

No. Your people make the call and sign off on it. The agents handle the reading, the extraction and the record behind it.

What does "AI you can check" mean?

Every value is linked to the file, page and version it came from, with a full history of who checked or changed it, and when. A reviewer can see where a number came from without re-reading the whole document.

Do we have to move our documents or replace our systems?

No. It works alongside the systems you already run. The 2026.2 release connects to SharePoint Online and M-Files, and anything else is scoped with you up front.

Can we use our own AI model?

Yes. Bring your own model and run it in your own cloud.

Is this only for life sciences, manufacturing and energy?

Those are the industries this session is built around, but the problem shows up in any regulated industry. Bring an example from yours to the Q&A.

See where the number came from. Then decide.

A live demo of AI on your documents that you can actually check.

Save your seat Can't make it live? Register and we'll send you the recording.
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