Search and RAG development
We build search and assistants that find the right answer inside your own content — grounded in your documents, citable back to the source — the kind of retrieval that holds up on the tenth question, not just the first demo.
A retrieval system is easy to demo and hard to trust. Anyone can wire up a question box that answers impressively once; the work is the part users actually feel — the answer that is right, comes from your content, and shows its sources so a person can check it. Without grounding and citations, a confident wrong answer is worse than no answer, because it is believed.
So we build the retrieval as the architecture, not the garnish — the chunking, the ranking, the grounding, and the honest "I don't know" when the content does not contain the answer. It is the same discipline that lets Memoria surface the right school circular or warranty out of a household's own records, in the language the family keeps them in.
What grounded retrieval needs
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Retrieval that actually retrieves
The unglamorous core — how content is chunked, embedded, and ranked — tuned on your real corpus, because a fluent answer over the wrong passage is just a confident mistake.
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Grounded and citable
Every answer tied back to the source it came from, so a person can verify it — and an honest "not found" when the content does not hold the answer, rather than an invented one.
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Built for your content
Search across your documents, records, and data in the languages and formats they actually live in — so the assistant is useful on the messy real corpus, not only a clean sample.
Related from Ekarche
Want answers from your own content?
Tell us what people need to find and where it lives. We will build retrieval that returns the right answer, grounded and citable — dependable past the first impressive question.