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Semantic Search

The Future of Search Is Semantic

Semantic search understands intentions instead of just keywords and delivers precise results, even when the exact terms are not known. This works in your company too.
Published on July 18, 2025 · by Michael J. Baumann

Nearly 80% of all Netflix content you watch comes from intelligent recommendations. You don't have to type «funny» and still find comedy gems. You also find bank heist movies when you search for «robbery» or «theft» instead of «bank heist».

The secret: Semantic search. This AI technology searches for meanings instead of keywords.

This hasn't reached many Swiss companies yet. Online shops still force customers to use keyword searches. Internally, employees comb through massive datasets with self-invented search terms – and find nothing.

This doesn't just cost unnecessary money. It's simply a shame. Because implementing semantic search isn't that difficult.

The Problem: Your Search Doesn't Understand You

Imagine this: A customer searches your online shop for «warm winter jacket for office wear». Your search engine finds nothing – yet you have dozens of business coats in stock. The customer leaves your site frustrated.

Or: Your sales representative needs documents from a similar project. She searches for «client project financial services» but can't find the documentation that's filed under «Banking-Solution». The proposal is delayed by days.

Traditional search systems are digitally thinking robots. They only understand exact word matches. Synonyms, context, or intentions remain foreign to them.

The Solution: Machines Learn Human Thinking

Semantic search works completely differently. The system doesn't just understand words, but their meaning. Search for «cost savings» and it also finds documents about «budget optimization», «efficiency improvements», or «expense reduction».

The technology behind it: Vector embeddings. Every word, every sentence is translated into a kind of mathematical coordinates. Similar concepts land close together in this digital space. «Dog» sits near «puppy», «four-legged friend», and «pet».

Your complete dataset is converted once into this vector form. After that, the system automatically understands connections that humans grasp intuitively.

Success Stories from Practice

The numbers speak for themselves:

  • Lacoste increased its conversion rate by 37%. Customers now find their «outfit for a beach vacation» without knowing exact product names.

  • Decathlon achieved 50% more conversions. Customers search for «equipment for outdoor adventures» and automatically find hiking boots, tents, and backpacks.

  • CERN in Geneva saves its researchers 15–20% of search time. The particle physicists find relevant datasets even without exact technical terms.

  • Even legal research tools benefit: Lawyers find judgments on «data protection violations» even when they only mention «privacy» or «GDPR».

What This Means for Your Company

Semantic search solves concrete business problems:

  • Customer service becomes more efficient: Your employees find answers in knowledge databases within seconds – even when they phrase the question differently than originally documented.

  • Sales accelerates: Proposals are created faster because similar projects are found automatically. «Digitization project» also finds «automation initiative» or «process optimization».

  • Online revenue increases: Customers find products even when they use different terms than your catalog. «Office chair for back problems» also finds «ergonomic workplace solution».

  • Project management works more smoothly: Teams access experiences from similar projects without spending hours searching for the right keywords.

  • Compliance becomes safer: Relevant regulations are reliably found – regardless of how the search is formulated.

The Technology Is Available

Semantic search can be implemented in any database and dataset – and seamlessly integrated into existing systems. We can usually deploy this technology directly on your existing infrastructure without requiring you to overhaul complete workflows. Such a custom-built search is often the best approach. But sometimes an external solution is sufficient, for example Azure AI Search from Microsoft, Algolia, or Google Cloud AI.

The question is no longer whether semantic search is coming. It's already here. The question is: When will you stop wasting time and money with outdated search systems?

Would you like to know how semantic search could work in your company? We'd be happy to show you the possibilities.

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