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Adlib releases Transform 2026.1 for regulated AI

Adlib releases Transform 2026.1 for regulated AI

Key Takeaways

  • Adlib Transform 2026.1 is a landmark release that bridges the gap between AI ambition and reality for regulated industries
  • The platform ensures accurate, validated, and traceable documents for AI systems
  • Five trust-reinforcing capabilities are introduced, including AI Model Builder, Object Separation, Source Citations, Human-in-the-Loop Classification Trigger, and Large Document Stitching
  • Transform 2026.1 includes five new standard connectors, such as the Veeva Vault Connector

Introduction to Adlib Transform 2026.1

Adlib Software has announced the general availability of Adlib Transform 2026.1, a platform designed to address the challenges of deploying AI in regulated industries, such as Life Sciences and Insurance. The primary issue faced by these industries is the lack of accurate, validated, and traceable documents that can be fed into AI systems.

The Problem with AI Deployment

AI models are no longer the bottleneck in AI deployment; instead, the quality of the data and documents being fed into these models is the major concern. Up to 80% of documents are not AI-ready, resulting in incomplete, inconsistent, and impossible-to-audit data. This can lead to hallucinations in clinical summaries, rejected insurance claims, and failed audits.

Trust-Reinforcing Capabilities

Transform 2026.1 introduces five key capabilities that reinforce trust in AI systems:

  • AI Model Builder from Sample Documents: Configures AI extraction models from sample documents in minutes, reducing the time-to-value for AI deployment
  • Object Separation in Pre-processing: Decomposes multi-modal documents into constituent elements, improving extraction accuracy by 20%
  • Source Citations in AI Chat with Documents: Provides full provenance for AI-generated answers, allowing for legal, compliance, and audit review
  • Human-in-the-Loop (HITL) Classification Trigger: Embeds human judgment at any classification or workflow step, creating a documented record of every correction
  • Large Document Stitching: Handles multi-hundred-page regulatory filings without performance degradation

Comparison of Document Processing Capabilities

Capability Description Improvement
AI Model Builder Configures AI extraction models from sample documents Reduces time-to-value from weeks to minutes
Object Separation Decomposes multi-modal documents into constituent elements Improves extraction accuracy by 20%
Source Citations Provides full provenance for AI-generated answers Enables legal, compliance, and audit review
Human-in-the-Loop Classification Trigger Embeds human judgment at any classification or workflow step Creates a documented record of every correction
Large Document Stitching Handles multi-hundred-page regulatory filings Eliminates performance degradation

New Standard Connectors

Transform 2026.1 introduces five new standard connectors, including the Veeva Vault Connector, which captures clinical documents from Veeva Vault, the system of record for over 1,000 Life Sciences companies.

Bottom Line

Adlib Transform 2026.1 is a significant release that addresses the challenges of deploying AI in regulated industries. By ensuring accurate, validated, and traceable documents, the platform reinforces trust in AI systems and enables organizations to deploy, scale, and defend AI in production. With its five trust-reinforcing capabilities and new standard connectors, Transform 2026.1 is an essential tool for organizations looking to unlock the full potential of AI.

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