Services · AI search
AI search and RAG for businesses
The knowledge you need already exists, but it is spread across documents, folders and systems, and held by a few colleagues. AI search lets your team ask a question in everyday language and receive a consolidated answer with a source instead of searching through links. Solvigo builds, launches and operates a solution tailored to your sources.
AI search is a way to ask questions of your company's knowledge in everyday language and receive a consolidated answer, rather than reviewing a list of results yourself. The underlying technique is RAG, Retrieval-Augmented Generation: the model first retrieves the most relevant passages from your documents and systems, then formulates its answer from them with source references. Solvigo builds search across your own data and operates it from the first conversation through to production.
What is RAG, and how does AI search differ from ordinary search?
The difference is what you receive. Ordinary search matches words and returns a list of documents for you to open, interpret and piece together. AI search interprets your meaning, retrieves the most relevant passages from your sources and summarises them into an answer with references.
RAG, Retrieval-Augmented Generation, makes this possible in two steps. First it retrieves the right material from your documents, often using vector search based on meaning rather than exact words. A question about a "notice period" can therefore find the right passage even when the contract says "termination of the agreement". The model then formulates its answer from that material. The answer is grounded in your own current documents rather than the model's general training data, and the risk of fabrication is substantially reduced because the answer can be traced to its source. This principle can support searches across projects, meetings and internal communication, with answers referring to your own material.
We take responsibility beyond the demo
AI search quality depends on finding the right passage even for a difficult, unusually phrased question, beyond the first ten test questions. That is why we own the entire delivery. We build around your own sources, including documents, intranets, contracts, cases and systems such as CRM and ERP, and configure retrieval to find the right passages for your questions. Quality is determined at this stage, long before the model starts writing, so this is where we focus our work.
We launch with your requirements in place: data stays in your own environment and can be kept within the EU, access follows existing permissions so no one receives answers from material they cannot view, and each answer shows its sources for human verification. Then we operate the solution, monitor answer quality and adjust it as your documents and business change. To see the full path from idea to production, read more about our AI implementation.
What it solves in practice
The value is greatest where knowledge exists but is scattered across many documents, different systems and a few experienced colleagues. That is where searching consumes time: someone searches folders for the right version of a contract, support looks for an answer a colleague has already written, a new employee does not know where to look, and a salesperson needs a figure from a document during a call.
For example, a customer service team receives the same questions repeatedly. The answers already exist in product documentation, contracts and old cases, but are spread across five places. The agent asks a question in everyday language and receives a consolidated answer linked to the exact passage behind it, ready to review and share. What previously took ten minutes of searching takes seconds, and the answer is more accurate because it comes from the source rather than memory.
This often provides the foundation for other capabilities. An AI agent needs to look up facts in your documents to make sound decisions, and AI automation of a workflow is only as good as the knowledge it can retrieve. The same search that answers employees' questions can therefore inform your automated processes.
Why Solvigo
AI search is only as good as the material it retrieves, and quality is determined at retrieval long before the model writes a word. We focus on your specific sources, permissions and the questions your employees actually ask. We measure success by whether answers are correct and useful in daily work, rather than how impressive a demo looks. We tell you if material needs organising before it can produce good answers, rather than assuming it will resolve itself.
How an engagement starts
We start with a question: what do you search for most often, and where is it stored? In a free initial conversation, we review where your knowledge lives today and select a focused collection of sources and a clear category of questions. We build a pilot on that material so you can assess the value and answer quality before expanding to more sources.
For a broader assessment of your opportunities, we also provide AI consulting in Stockholm and look at the full flow of information, beyond search alone. Tell us where your knowledge is stored today, and we will show how your team could find answers in seconds rather than minutes.
Meet Solvigo Insights
Alongside custom AI solutions, we develop Solvigo Insights. The product helps you understand what people actually think through in-depth conversations and a combined analysis of their responses.
Frequently asked questions
What is RAG (Retrieval-Augmented Generation)?
RAG means the model first retrieves relevant passages from your own documents, then writes its answer based on them. It reads your sources first and grounds its answer in them rather than relying on its general knowledge. This makes answers current, specific to your business and traceable to their source documents.
What is AI search and how does it differ from ordinary search?
AI search lets you ask a question in everyday language and receive a consolidated answer instead of a list of links to investigate yourself. Ordinary search matches words and leaves the interpretation to you. AI search interprets your meaning, retrieves the right passages from your documents and summarises them with references to the sources.
Does RAG reduce the risk of hallucinations?
Yes, significantly. Because the answer is based on passages actually retrieved from your documents, the model has evidence to draw on instead of guessing. Each answer also shows its sources so a person can check it quickly. This does not remove the risk entirely, but it is the most effective method we know for keeping answers grounded in facts.
Can AI search our own internal documents?
Yes, that is its purpose. Search connects to your own sources: documents, intranets, wikis, email, cases, contracts and systems such as CRM and ERP. Your data stays in your own environment and can be kept within the EU. Access follows your permissions, so people only receive answers from material they are authorised to see.
What is the difference between enterprise search and AI search?
Traditional enterprise search indexes content and returns a list of results for you to review. AI search builds on that idea, but interprets the question semantically and delivers an answer with sources rather than just links. RAG enables this: retrieve the right material first, then formulate the answer from it.