Supply Chain AI & Data Engineering

OVERVIEW

What we do

Digital business transformations and AI adoption in supply chain management start and end with data. Quality data. Historical data. Connected data. However, it’s really the organizational change management and cross-functional collaboration that make AI-driven initiatives successful.

Our supply chain data science and applied supply chain technology experts help IT and supply chain leaders alike demonstrate tangible ROI and build momentum. From data architecture strategy and governance to developing business-specific AI applications, we guide you every step of the transformation journey.

OFFERINGS

How we can help

AI Readiness Assessment & Roadmap

Evaluate your capability requirements, identify gaps, and define future roadmaps to deploy supply chain AI capabilities

Supply Chain Data Platform Architecture & Implementation

Create the foundational end-to-end data platform to connect structured and unstructured, internal and external supply chain data to enable connected planning, execution, visibility, and advanced AI analytics

Supply Chain Data Governance Strategy

Define the processes, policies, and metrics to ensure consistent and trusted data across the supply chain and how it aligns with the organization as a whole

AI Supply Chain Platform Selection & Implementation

Determine which solution(s) are best suited for your current and future supply chain along with deployment expertise

Cloud Migration: Edge Computing Strategy & Adoption

Transition from on-premises to cloud or enable industrial IOT with hyper-scalers to align your systems with your data and business priorities

Supply Chain AI Application Enablement

Build and implement business-specific AI applications such as demand sensing and forecasting, WES & WCS system maintenance, and agentic AI 