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Blog
Here’s an overview of our latest blog posts on enterprise search and artificial intelligence.
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Enterprise Search with Chatbot and RAG explained
03/25/2026
Enterprise Search makes information across companies and public-sector organizations findable. Internal chatbots and AI assistants build on this foundation to generate reliable answers and summaries from approved internal sources. This article explains how Enterprise Search and RAG work together, which use cases are most common, and what matters for security, governance, and implementation.
Blog
25.03.2026
Enterprise Search with Chatbot and RAG explained
Enterprise Search makes information across companies and public-sector organizations findable. Internal chatbots and AI assistants build on this foundation to generate reliable answers and summaries from approved internal sources. This article explains how Enterprise Search and RAG work together, which use cases are most common, and what matters for security, governance, and implementation.
Blog
17.02.2026
Introducing GenAI in Public Sector: secure and trusted
Generative AI enables administrations to make processes more efficient and reduce the workload for skilled staff. Successful AI implementation requires secure technology and acceptance by teams. This blog highlights the issues that concern employees when it comes to GenAI and shows how administrations can build trust and achieve quick wins.
Blog
27.01.2026
Use knowledge productively with enterprise search and generative AI
Organizations face the challenge of making ever-growing amounts of information from many systems quickly, securely, and with the right context. At the same time, content should not only be found but also understood and put to productive use. The AI software trio from IntraFind – iFinder, iAssistant, and iHub – addresses precisely these requirements and supports companies and public authorities in using knowledge efficiently and integrating generative AI securely into their everyday work.
Blog
07.01.2026
AI Trends 2026: From the experimental phase to productivity
2025 was a year of high expectations: new AI models of all sizes, major reasoning breakthroughs, and growing availability of generative AI across enterprises. Yet the flood of proof-of-concepts also revealed that not every idea holds up in practice. 2026 will therefore not be defined by the next hype, but by a readjustment: What really works? Where is measurable added value created? What can be reliably operated and monitored in daily work? The following trends are shaping this phase:
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