{"id":87749,"date":"2026-09-08T15:45:00","date_gmt":"2026-09-08T13:45:00","guid":{"rendered":"https:\/\/fhi.nl\/nieuws\/the-corporate-brain-why-ai-in-industry-is-decided-at-the-data-layer-2\/"},"modified":"2026-09-08T15:58:38","modified_gmt":"2026-09-08T13:58:38","slug":"the-corporate-brain-why-ai-in-industry-is-decided-at-the-data-layer-2","status":"publish","type":"news","link":"https:\/\/fhi.nl\/en\/news\/the-corporate-brain-why-ai-in-industry-is-decided-at-the-data-layer-2\/","title":{"rendered":"The corporate brain: why AI in industry is decided at the data layer"},"content":{"rendered":"
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\n\t\t\t\t\tThe corporate brain: why AI in industry is decided at the data layer\t\t\t\t<\/h1>\n\n\t\t\t\t
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amber at the World of Industry, Technology & Science, 22 to 25 September 2026, Jaarbeurs Utrecht<\/strong><\/p>\r\n

Industry, electronics and laboratory environments produce knowledge every single day: test reports, design revisions, maintenance logs, quotes, deviations, approvals. It resides in file shares, in the DMS, in the ERP, in ticketing systems and in mailboxes. And it sits in the heads of the colleagues who will retire over the next few years.<\/p>\r\n

This is exactly where many AI projects come apart. Not at the model, but at the layer underneath it. According to IDC, 88 percent of AI pilots never make it into production. An assistant that summarizes documents you had to find yourself does not solve the actual problem.<\/p>\r\n

Starting one layer deeper<\/h2>\r\n

amber calls that missing layer the corporate brain. It is not a marketing metaphor but a data layer between your sources and your AI: a prepared, understood copy of what an organization knows.<\/p>\r\n

The difference to classic search lies in understanding. A keyword search returns matches. A data layer recognizes relationships: which document is the final version, which project and which asset a test report belongs to, which approval currently applies. Knowledge is processed semantically once, instead of running through every system again with each new question. That improves answer quality and keeps the cost per answer stable as usage grows.<\/p>\r\n

Permissions are part of the architecture rather than a filter applied afterwards. Existing access rights from your IT landscape are carried over, along with recency and provenance for every piece of information. Everyone sees what they are already allowed to see, and can trace where an answer comes from.<\/p>\r\n

From answers to action<\/h2>\r\n

The applications people actually work with sit on top of this foundation: AI search across system boundaries, assistants for recurring tasks, and agents that take over routine steps. The value does not come from another tool, but from the fact that every application draws on the same knowledge base.<\/p>\r\n

More than 70 connectors are available for integration, including Microsoft 365, Confluence, Jira and Salesforce, alongside file shares, DMS and ERP systems.<\/p>\r\n

Sovereignty is an architectural question<\/h2>\r\n

Preparing your knowledge centrally creates a valuable asset. That makes it important who can access it and which legal jurisdiction it sits in. amber is GDPR and ISO 27001 compliant and operated in Europe. Customer data is not used to train AI models.<\/p>\r\n

About amber<\/h2>\r\n

amber Tech GmbH, based in Aachen, builds business AI that makes internal knowledge securely accessible and combines search, assistance and automation. The team has been working on this since 2021.<\/p>\r\n

At WOTS, amber will show concrete examples of how a data layer takes shape in grown IT landscapes, and what becomes possible once it exists.<\/p>\t\t<\/div>\n\t<\/div>\n<\/div>\r\n\t

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