AI demand forecasting, inventory optimisation, and real-time supply chain visibility — built as production systems, not slide decks. Our supply chain AI consultants unify your ERP, MES, and SCM data and ship working machine learning in 3–8 weeks.
A supply chain AI consultant finds where machine learning creates measurable value — demand forecasting, inventory optimisation, and real-time visibility — then builds and deploys the production systems to deliver it. Agility unifies data from ERP, MES, and SCM platforms, trains the models, and ships in 3–8 weeks. In a real deployment for a multi-site manufacturer we reached 88% prediction accuracy, cut safety stock by 40%, and reduced carrying costs by 35%. See our demand forecasting case study.
Four capability areas — each grounded in production deployments, not demos.
Ensemble machine-learning models trained on unified enterprise data that forecast demand across product lines — accounting for seasonality, promotions, and volatility.
ML-optimised stock levels that free up working capital without hurting availability — balancing service levels against carrying cost.
Real-time dashboards and streaming pipelines that give planners a single view across product lines, sites, and systems.
We connect the systems you already run into one analytics-ready foundation — the groundwork every reliable supply chain model depends on.
A mid-sized manufacturer operating across multiple product lines replaced spreadsheet forecasting with an AI platform on Azure Machine Learning and Databricks.
From first call to production in 3–8 weeks — no unnecessary steps.
Free call to understand your supply chain, data maturity, and the forecasting or inventory problem worth solving first.
Fixed or T&M proposal with timeline and milestones, delivered within 48 hours.
Senior engineers integrate your data, train the models, and ship — with weekly demos and full code access.
Live in 3–8 weeks with dashboards, documentation, training, and optional ongoing support.
A real multi-site manufacturing deployment: 88% prediction accuracy, 40% safety-stock reduction, 35% lower carrying cost.
We ship working supply chain AI in 3–8 weeks — not multi-month advisory engagements that end in a deck.
SAP, Oracle SCM, Siemens MES, Databricks, Azure ML, Kafka — we integrate the stack you already run.
The engineer building your forecasting platform is on the project from day one — no hand-offs to juniors.
A supply chain AI consultant identifies where machine learning creates measurable value across your supply chain — demand forecasting, inventory optimisation, and real-time visibility — then builds and deploys the production systems to deliver it. Agility unifies data from ERP, MES, and SCM systems, trains forecasting models, and ships working software in 3–8 weeks rather than long advisory engagements.
The highest-ROI supply chain AI use cases are demand forecasting, inventory and safety-stock optimisation, and supply chain visibility. In a real deployment for a multi-site manufacturer we reached 88% prediction accuracy in targeted demand scenarios, reduced safety stock by 40% while maintaining service levels, cut inventory carrying costs by 35%, and reduced forecast preparation from days to hours — virtually eliminating stock-out incidents.
Traditional forecasting relies on spreadsheets and single-method statistical models that struggle with promotions, seasonality, and demand volatility. AI demand forecasting uses ensemble machine-learning algorithms trained on unified data from all enterprise systems, producing more accurate, faster forecasts. Our manufacturing deployment delivered an 88% improvement in forecast accuracy and moved forecast preparation from days to hours.
We integrate the systems you already run. Our forecasting platform for a mid-sized manufacturer unified data from SAP ERP, Siemens MES, and Oracle SCM into a Databricks Delta Lake, with Azure Machine Learning for the models, Azure Data Factory and Kafka for streaming, and Power BI for supply chain visibility. We handle the data engineering and feature work as part of the engagement.
Agility deploys production supply chain AI in 3–8 weeks depending on scope and data readiness. You get a scoped, fixed or T&M proposal within 48 hours of a discovery call, weekly demos throughout the build, and handover documentation at go-live — with senior engineers on the project from day one.
Tell us your forecasting or inventory challenge. We'll scope a plan in 48 hours.
Talk to a Supply Chain AI Consultant