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Devatis Goes Live on TraceLink MINT to Prepare for Agentic Order-to-Cash Operations

TraceLink logo (PRNewsfoto/TraceLink)

News provided by

TraceLink, Inc.

Apr 20, 2026, 10:00 ET

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By digitalizing core commerce transactions with customers, Devatis aims to improve OTIF, reduce stockouts, and prepare for an AI agent-driven supply chain

Devatis has gone live on TraceLink's Multienterprise Information Network Tower (MINT) to digitalize its end-to-end order-to-cash operations. By moving beyond fragmented EDI integrations to an Integrate-Once™ network model, Devatis can exchange orders, shipment data, invoices, and financial transactions across its trading partner ecosystem through a single link. Building on its existing foundation in global track-and-trace, Devatis is further unifying business transactions on a shared digital network, creating a consistent, real-time flow of data across partners. This establishes the data, metadata, and knowledge foundation required to enable TraceLink's no-code enterprise AI agents to operate as governed users across its supply chain.

BOSTON, April 20, 2026 /CNW/ -- TraceLink, the world's largest Agentic Business Network, today announced that Devatis, the U.S. affiliate of global pharmaceutical manufacturer Deva Holding A.Ş., has gone live on TraceLink's Multienterprise Information Network Tower (MINT).

With its MINT deployment, Devatis has replaced fragmented point-to-point EDI integrations with a network model linking wholesalers, 3PL providers, and other trading partners. This shift centralizes order, warehouse, shipment, and invoice transactions on a shared network, creating a real-time operational record of order-to-cash activities across a diverse trading partner network.

Scaling Order-to-Cash Operations Across a Growing Partner Network

As Devatis expanded its U.S. commercial operations, managing order-to-cash transactions across a growing number of trading partners introduced operational complexity, including:

  • Order processing and fulfillment relied on a combination of EDI integrations, manual validation steps, email communications, and spreadsheet tracking.
  • Teams frequently reconciled discrepancies between systems, confirmed shipment and invoice details manually, and coordinated issue resolution across multiple partners.
  • Onboarding new trading partners required custom EDI mapping, testing, and configuration--often extending onboarding timelines by months.

As the number of partners and transaction volumes increased with U.S. market expansion, this traditional point-to-point integration model limited Devatis' ability to scale commercial activity efficiently.

Transforming Order-to-Cash into a Network-Based Process

To modernize and scale its order-to-cash operations, Devatis implemented TraceLink MINT and adopted the Integrate-Once™ model, establishing a single link that enables consistent data exchange across its trading partner network. This builds on Devatis' existing foundation with TraceLink, including global pharmaceutical compliance, track-and-trace, and serialization capabilities, which established trusted, regulated data exchange across its supply chain. Through this network-based framework, Devatis can now exchange transactions with all trading partners, which also equally benefit through a single, no-cost link to the network--eliminating the need for separate integrations with each trading partner.

This implementation links:

  • Customer order capture
  • 3PL warehouse execution updates
  • Shipment visibility and confirmation
  • Invoicing
  • Financial reconciliation

Because new partners can link through the existing network, onboarding timelines have been reduced to as little as three days. This new capability enables Devatis to accelerate time-to-revenue, enter new markets faster, and scale its commercial operations without adding integration complexity.

Building the Operational Foundation for Agent-Driven Supply Chains

Centralizing order-to-cash transactions through the TraceLink network also lays the foundation for Devatis to introduce automated monitoring and agentic decision support in the future. As operational data flows through the shared digital framework, AI agents can be layered onto these processes to monitor activity across systems and partners, identify discrepancies, validate transactions, and flag anomalies.

Initial agentic AI use cases being explored include:

  • Price validation -- automatically comparing incoming purchase orders with approved pricing contracts to detect discrepancies before fulfillment
  • Order monitoring -- identifying orders that stall between systems or partners and flagging them for investigation
  • Shipment reconciliation -- comparing order, warehouse, and shipment transactions to identify mismatches between ordered and shipped quantities
  • Forecast monitoring -- comparing real-time orders with distributor forecasts to identify demand changes that could affect inventory levels
  • Operational anomaly detection -- identifying unusual ordering patterns or price changes across trading partners

These capabilities allow routine coordination and monitoring tasks--traditionally handled through manual oversight--to be performed continuously across the network on a governed basis with a "human-in-the-loop" model, as desired.

Executive Perspective

"Digital supply chain operations depend on real-time data flowing across partner and internal systems," said Shabbir Dahod, President and CEO of TraceLink. "By moving order-to-cash transactions onto a shared network, Devatis now has a consistent operational record of orders, shipments, and invoices across partners. That visibility enables automated monitoring and coordination that would be difficult to achieve in fragmented integration environments. Critically, the Devatis team is now establishing a rich foundation of real-time data, metadata, and knowledge required to power AI agents."

"The TraceLink network model allows us to scale operations without adding integration overhead," said Mike Dougan, Head of Sales, U.S., Devatis. "It simplifies how we integrate with trading partners and gives us clearer visibility into order and fulfillment activity. Over time, it also creates opportunities to introduce agentic automation that helps our teams detect issues earlier and manage operations more efficiently."

Learn how TraceLink MINT enables companies to digitalize partner transactions and establish the foundation required for agentic end-to-end supply chain orchestration.

About Devatis 
Devatis is a pharmaceutical company delivering excellence in every dose. With a broad portfolio of high-quality medicines, the company operates under the highest EU GMP and U.S. FDA standards, ensuring consistent quality and reliability across all its markets.

About TraceLink
TraceLink is the world's largest Agentic Business Network, enabling life sciences and healthcare companies to build and manage a scalable digital workforce of governed, no-code AI agents that execute and coordinate mission-critical supply chain operations alongside human teams.

Powered by the Integrate-Once™ OPUS platform, which links 300,000+ authenticated network entities that exchange hundreds of billions of product transactions annually, only TraceLink delivers the industrial foundation required to develop, train, and continuously optimize agentic supply chain talent--governed AI agents--operating across multienterprise processes.

This agentic workforce model redefines how work gets done--expanding capacity, accelerating execution, and enabling safe, secure supply chain ecosystems that serve the greater good and operate with unprecedented agility, intelligence, and productivity beyond the limits of human-only operations, ensuring patients receive safe, high-quality therapies and products when and where they are needed.

Learn more at www.tracelink.com

SOURCE TraceLink, Inc.

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TraceLink, Inc.

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  • TraceLink Launches OPUS Agents and Creates a New Paradigm for Supply Chain Management: Agentic Business Networks

  • TraceLink VP of OPUS Core Platform Development Jerry Meyer Named a 2026 Supply & Demand Chain Executive "Pros to Know" Honoree

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