TechDogs-"Kinaxis Partners With Databricks To Accelerate AI-Powered Supply Chain Orchestration"

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Kinaxis Partners With Databricks To Accelerate AI-Powered Supply Chain Orchestration

By Business Wire

Business Wire
Overall Rating

Kinaxis Maestro™ and Databricks’ Data Intelligence Platform come together to power faster insights, unified data, and scalable AI across global supply chains

OTTAWA, Ontario & SAN FRANCISCO--(BUSINESS WIRE)--Kinaxis® (TSX:KXS), a global leader in end-to-end supply chain orchestration, and Databricks, the data and AI company, today announced a partnership to set a new standard for intelligent supply chain decision-making.

By combining Kinaxis Maestro™, the only AI-native platform purpose-built for end-to-end supply chain orchestration, with the scalability and governance of the Databricks Data Intelligence Platform, the companies are enabling organizations to unify their data, accelerate AI adoption, and respond to change with speed and confidence.

This collaboration meets growing demand for more agile, data-driven supply chains. It strengthens Maestro’s supply chain data fabric, helping companies bring together information from core systems like inventory and procurement, alongside external inputs such as weather patterns and market signals, all within one governed environment. The result is faster insights, greater execution agility, and a more resilient, innovation-ready supply chain.

“Global supply chain organizations are dealing with more data than ever, but it’s often fragmented across systems, making it difficult to act quickly or consistently,” said Andrew Bell, chief product officer at Kinaxis. “This partnership strengthens the data fabric that powers Maestro™, accelerating our AI innovation agenda and enabling faster, smarter decisions at scale. Together, we’re giving businesses the ability to orchestrate their supply chains with the intelligence and speed today’s disruptions demand.”

Purpose-Built for Supply Chain Performance
Maestro was built specifically for supply chain orchestration, embedding domain-specific intelligence into every layer of the platform designed to drive planning, execution, and decision-making. With the Databricks Data Intelligence Platform powering its underlying data infrastructure and Delta Sharing powering seamless, secure, cross-platform data sharing, companies can integrate once and leverage that data across every function - reducing silos, eliminating duplication, and enabling predictive, generative, and autonomous AI at scale.

Maestro already powers millions of simulations annually to help companies manage volatility. Now, with Databricks’ elasticity and scale, it can process even more complex data environments without compromising trust. Databricks offers enterprise-grade data controls, while Kinaxis ensures decisions are backed by explainable AI that remains traceable and auditable.

“Supply chain data is among the most complex and operationally critical in the enterprise, but it is critical to help organizations build data intelligence,” said Shiv Trisal, Global Manufacturing, Transportation & Energy GTM Leader at Databricks. “By partnering with Kinaxis, we’re helping companies centralize data and shift from fragmented insights to real-time, intelligent actions that power their enterprise AI strategy.”

Turning Data into Decisions Faster
In modern supply chains, agility is everything. With Kinaxis and Databricks working in sync, organizations gain a shared intelligence layer that connects their entire supply chain ecosystem. This allows them to respond to disruption, whether it’s a demand spike, supplier issue, or market shift, with speed and precision.

Unlike legacy systems that require full dataset reprocessing, Maestro only recalculates what’s changed. That means businesses get faster decisions, clearer insights, and better outcomes, without the lag or data overhead.

A New Standard for Intelligent Supply Chain Orchestration
This partnership goes beyond integration. Kinaxis and Databricks are working together to reduce fragmentation, embed intelligence across every supply chain stage, and unlock a new level of responsiveness, from strategic planning to execution on the ground.

As supply chains continue to evolve, this collaboration positions both companies to lead the next era of AI-powered transformation, where decisions are faster, disruptions are less disruptive, and performance is driven by unified data.

About Kinaxis
Kinaxis is a global leader in modern supply chain orchestration, powering complex global supply chains and supporting the people who manage them, in service of humanity. Our powerful, AI-infused supply chain orchestration platform, Maestro™, combines proprietary technologies and techniques that provide full transparency and agility across the entire supply chain — from multi-year strategic planning to last-mile delivery. We are trusted by renowned global brands to provide the agility and predictability needed to navigate today’s volatility and disruption. For more news and information, please visit kinaxis.com or follow us on LinkedIn.

Source: Kinaxis Inc.


Contacts

Media Contacts
Matt Tatham | Kinaxis
mtatham@kinaxis.com
+1 917.446.7227

Investor Relations
Rick Wadsworth | Kinaxis
rwadsworth@kinaxis.com
+1 613-907-7613

Frequently Asked Questions

What is the partnership between Kinaxis and Databricks?

Kinaxis and Databricks have partnered to integrate Kinaxis Maestro, an AI-native supply chain orchestration platform, with the Databricks Data Intelligence Platform. This collaboration aims to enhance supply chain decision-making through unified data and scalable AI.

How does this partnership benefit businesses?

The partnership enables faster insights, greater execution agility, and a more resilient supply chain by unifying data from various sources, accelerating AI adoption, and improving responsiveness to change.

What are the key features of this integrated solution?

Key features include a unified data layer, faster decision-making through reduced recalculation times, and enterprise-grade data controls, enabling predictive, generative, and autonomous AI at scale.

First published on Wed, Apr 2, 2025

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