AI Native Solutions to Enhance Business Outcomes
In an announcement made at the Kinexions global customer conference in Las Vegas on June 2nd, Kinaxis Inc., a leader in supply chain planning, introduced Forward Deployed Engineering (FDE). This new model helps enterprises operationalize AI for better business outcomes.
Using the Maestro platform, the FDE model aims to translate AI-driven decisions into measurable outcomes. Integrating a unified data foundation with semantic intelligence, this approach improves coordination across enterprise operations.
Razat Gaurav, CEO of Kinaxis, stated, “The challenge companies face is no longer simply making better decisions faster, it’s ensuring those decisions drive real outcomes.” He emphasised the importance of grounding AI in enterprise operations to transition from isolated decisions to continuous execution.
Transforming Traditional Models
Unlike traditional planning models, the FDE engagement model focuses on business impact rather than predefined requirements. The model prioritises long-term value over short-term project goals, aiming to build scalable solutions that can continuously improve.
Embedding agentic AI into workflows, Kinaxis enables new collaborative methods between teams and AI. Organisations can sense, reason, decide, and act within real-world business contexts through this integration.
Starting from Kinexions, the FDE model will be available through Kinaxis account teams for selected customers. A customer and partner hackathon was also announced to accelerate the development of AI-driven solutions tailored to real business challenges.
FDE’s introduction represents a shift in engagement models from features to business outcomes. It moves from project-based to product-based solutions and from initial deployment to sustained ownership.
Kinexions, the company’s annual global customer conference, featured a keynote by CEO Razat Gaurav. Livestreamed globally on June 2 at 11:30 am EST via LinkedIn Live, the event highlighted the importance of operational orchestration.
This approach coordinates signals, decisions, actions, and learnings across various business processes. Combining AI, organisations can transition from isolated decision-making to coordinated execution, connecting data, systems, teams, and actions across the enterprise.
Traditional planning models often result in fragmented decisions. Concurrent planning introduced synchronized, cross-functional decision-making across supply chain processes. Operational orchestration extends these principles to create adaptive organisations that align, respond, and improve continuously.
Razat Gaurav commented, “The next shift is ensuring decisions translate into coordinated action across the business. That only happens when AI is grounded in the physics of enterprise operations.” With this context, organisations transition from isolated decisions to continuous execution at scale.
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Last updated: 29 June 2026, 11:56 am
