A leading global chemical producer wanted to generate additional revenue from its top 25 customers. However, account managers lacked visibility into more than one million products distributed across approximately 20 planning units, limiting their ability to identify relevant cross-sell and upsell opportunities.
Altimetrik created a Single Source of Truth that unified product, customer, sales, and market data. Machine learning algorithms analyzed this information alongside geographic restrictions and customer spending capacity, generating actionable recommendations through an intuitive dashboard.

A US refrigeration equipment manufacturer manages temperature monitoring across more than 2,500 retail stores manually. The approach drove high equipment downtime, escalating maintenance costs, and left the client unable to control business-critical operations remotely. Altimetrik built a SaaS store monitoring platform with multi-site control, real-time temperature tracking, and detailed alarm/activity history. It added secure role-based remote diagnostics and CRM integration that auto-generates work orders from business rules, replacing manual monitoring with centralized, data-driven operations across the store estate.

A Fortune 100 manufacturer was losing product and revenue to refrigeration equipment failures across a massive global cold chain fleet. Scarce technicians, long container waits at dock locations, and $150B industry-wide food waste annually made reactive monitoring untenable. Altimetrik co-created a Microsoft Azure cold chain solution that processes data from 100,000+ global containers using predictive algorithms across 40+ factors and 10 alarm types, enabling real-time intervention to prevent spoiled shipments.

A leading machine tools and textile machinery manufacturer needed to meet growing customer demand for greater automation, driven by operator skill gaps and the need to reduce labour dependency. At the same time, competitors were differentiating their offerings by embedding AI/ML capabilities directly into their machines.
Altimetrik helped the manufacturer define and execute an enterprise-wide AI strategy, beginning with an AI readiness assessment, competitor benchmarking, and use-case prioritization. This was translated into an actionable roadmap across data, technology, and talent, followed by the deployment of edge AI solutions across its machine tool and textile machinery portfolios and a GenAI-powered intelligent service centre.

A global biopharmaceutical company operating in more than 80 countries needed to improve visibility and decision speed across its complex manufacturing network. Operational data was fragmented across multiple systems, forcing teams to spend significant time consolidating information before acting.
Altimetrik developed a Generative AI-powered manufacturing intelligence solution on AWS. The platform unified structured and unstructured data and enabled users to retrieve real-time insights through natural-language conversations. This accelerated operational decisions and created opportunities for substantial production and supply-chain savings.

A premium apparel company needed to integrate machine learning into merchandising and planning decisions across assortment, procurement, replenishment, and sales. Disconnected forecasting models, lengthy experimentation, and limited production controls prevented the business from using predictive intelligence effectively.
Altimetrik developed a cloud-native MLOps platform that integrated model development, deployment, monitoring, and retraining with the client’s data ecosystem. The solution accelerated production releases, improved forecast accuracy, and enabled agile inventory decisions across regions and channels.

One of North America’s largest premium fresh-tomato growers needed to improve six-week yield forecasting across its year-round greenhouse operations. Manual planning relied heavily on individual expertise, resulting in inconsistent forecasts and limited use of available production data.

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