Sectors and cases
The best technology is the one that understands the problem you need to solve
Each sector starts from a business need. The front shown is where the operation usually starts learning. Select a sector to see its solutions and cases.
CasesReal results, sector by sectorThe challenge, what was done and the result of data and AI projects at large companies.38case studies published7sectors, plus cross-sector casesSee the cases
Financial services · Data and AI
“How do we make better decisions without taking on more risk?”
Financial services: credit, risk and fraud decisions backed by reliable data, with an audit trail and explicit rules.
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Retail and consumer goods · Business processes
“How do we understand the customer better and run leaner?”
Retail: demand forecasting, service resolved in the first conversation, and replenishment that keeps up with the real store.
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Manufacturing and automotive · Data and AI
“How do we produce better, predict problems and cut waste?”
Manufacturing and automotive: plant data with context, maintenance ahead of failure, and integration across engineering, production and aftersales.
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Health and pharma · Security and governance
“How do we use data and intelligence to improve journeys and operations?”
Healthcare: clinical and operational information organized, with privacy, governance and decision support for the people providing care.
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Energy and utilities · IT operations
“How do we modernize network operations and respond faster to every incident?”
Energy and utilities: a digital asset inventory, real-time network management and more productive field teams.
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Telecommunications · IT operations
“How do we run complex networks with quality and serve millions of customers efficiently?”
Telecommunications: 24×7 operation of critical infrastructure, customer service with AI agents, and integrated customer and network data.
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Public sector · Data and AI
“How do we deliver better services to citizens and run more efficiently?”
Government: accessible digital services, auditable operations and responsible use of public data.
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Logistics · Business processes
“How do we make complex operations more predictable, safer and smarter?”
Logistics: end-to-end visibility, exceptions handled by agents, and delivery dates the customer can trust.
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Agribusiness · Data and AI
“How do we turn data and technology into productivity and predictability?”
Agribusiness: field, weather and operational data in one place, supporting crop and logistics decisions.
See solutions for this sector →Every sector has its own bottleneck
The method does not change: we understand the problem, map the workflow, check what already exists and define a first step with real impact.
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