gensai.aiGensai designs AI answer engines: next-generation search engines that understand natural language and answer directly from your data, documents and business databases, powered by RAG (Retrieval-Augmented Generation).
An answer engine does not return a list of links: it answers. Users ask their question the way they would ask a colleague and get a precise, written answer grounded in your content. Semantic search retrieves the relevant passages even when the words differ, reranking sharpens relevance, and the model generates the answer while citing its sources.
Every engine is built on your data: internal documentation, catalogues, regulatory bases, FAQs, records. The RAG architecture grounds answers in this verified content, which eliminates most hallucinations: the engine only answers on what it knows, and knows how to say it does not know.
Confidentiality drives the architecture: depending on your requirements, the whole system is hosted on a sovereign cloud, on your own servers or even fully locally, with open models. Your documents are never used to train third-party models, and your users' access rights are enforced on every query.
Use cases
Internal knowledge base
Your teams query HR, IT or quality procedures in natural language and get the right answer immediately.
Automated customer support
A smart FAQ that actually answers: fewer tickets, self-sufficient customers, a support team freed from recurring questions.
Regulatory intelligence
Querying legal and normative bases by sector and company size, with answers sourced article by article.
E-commerce product search
The customer describes a need, the engine understands the implicit criteria and suggests the matching catalogue products.
Visitor information
Opening times, prices, access, programme: a tourist office, museum or leisure park answers in every language, from its official content.
Trade show assistant
Programme, speakers, access maps: attendees of a professional event find everything in one question.
Archives and collections
Exploring a documentary collection, archives or heritage holdings by meaning, not just keywords.
Quote and sales support
A virtual expert that knows your products, prices and history: faster, better-qualified quotes.
Our references
Frequently asked questions
What is an answer engine?
An answer engine is a search engine augmented with generative AI: instead of returning links, it writes a direct answer from the relevant documents, citing its sources. It combines semantic search, RAG and a language model.
How is it different from a classic search engine?
A classic engine indexes keywords and returns pages. An answer engine understands the intent of the question, retrieves relevant passages by meaning and formulates an immediately usable answer, even when the question's words do not appear in the documents.
How do you avoid hallucinations?
Answers are grounded in your content through RAG: the model only answers from retrieved passages, cites its sources and knows how to say it does not know. Reranking steps and evaluation sets measure reliability before production.
Does my data stay confidential?
Yes. Depending on your requirements, the engine is deployed on a certified sovereign cloud, on your own servers (On Premise) or even fully locally. Your documents are never used to train third-party models.
An answer engine project?
Let's talk about your data and your users: Gensai proposes a concrete path, from POC to production.