Search & Information Retrieval

Traditional keyword search is being augmented and in some cases replaced by AI-powered systems that understand the meaning behind your query rather than just matching words. Retrieval-augmented generation (RAG) combines search with language models - finding relevant documents and then synthesising an answer from them rather than simply returning a list of links. This approach powers the AI features appearing in search engines and enterprise knowledge management tools. For many queries, getting a direct synthesised answer is genuinely faster and more useful than scanning through ten blue links. The trade-off is transparency. When a search engine returns links, you can evaluate the sources yourself. When an AI synthesises an answer, you are trusting it to have found the right sources and represented them accurately - and you may not see where the answer came from. AI search systems can also inherit the biases of their training data, surface outdated information, or confidently present incorrect answers. For your business, AI-enhanced search is most valuable for internal knowledge bases and well-defined information retrieval tasks where the source material is controlled and verifiable.