Memraiq
About Memraiq
Hosted knowledge workspace in private beta: we help teams get grounded answers from their own text documents, with a clear path to richer formats.
Mission
Make organisational knowledge easy to search, reason over, and trust.
Teams generate enormous amounts of internal knowledge — runbooks, policies, design decisions, meeting notes. Most of it becomes unsearchable the moment it's written. Memraiq exists to change that: upload your documents, and your team can ask questions and get answers that are grounded in what you've actually written — not model guesses.
The product
A private AI knowledge base, not a chatbot
Memraiq is built for teams that need answers from their own text documents today — Markdown and plain text — with richer file support launching soon. It is different from generic AI chat: responses are grounded in what you've uploaded and indexed, not the model's training data. The model provides structure and language; your content provides the facts.
Under the hood, Memraiq combines vector semantic search with a knowledge graph built by LightRAG — so retrieval understands entity relationships and document structure, not just text similarity. This means better answers for multi-hop questions, and fewer hallucinations overall.
We prioritise grounded answers, citations you can check, and straightforward onboarding. Workspace roles and isolation keep knowledge inside the right team.
Who it's for
Teams that depend on internal knowledge
Engineering teams
Runbooks, architecture decisions, postmortems, onboarding guides. Ask about system behaviour, not Google it.
Operations teams
Policies, SLAs, escalation paths, vendor contracts. Get clear answers with citations your team can verify.
Knowledge workers
Research, reports, meeting notes, strategic docs. Surface relevant content across large document collections.
Built by
Ri-Tech
Memraiq is built and operated by Ri-Tech, a small technology company based in Ghana. We build tools that prioritise clear architecture, observable systems, and documented behaviour over vague AI promises. The platform is real, deployed, and in use at app.memraiq.com.
Grounded
Answers reference real sources. The model doesn't invent facts.
Transparent
We are clear about what the product does today versus what is on the roadmap — plus citations and honest plan limits.
Operational
Built for teams running real workloads, not just demos.
Questions? We're happy to talk about the product or your use case.