Turn your team’s knowledge into a queryable AI
Employees, agents, and customers get grounded, cited answers from the documents and systems you already have.
Talk to us about your document volumeWays companies put their documents to work
Hyppe’s RAG platform ingests your knowledge and answers in real time with citations. No search engineering, no vector-DB project.
Knowledge base assistant
A RAG assistant that answers from your company policies, manuals, and wikis — with citations.
Internal wiki & handbook search
One queryable index over your internal wikis and onboarding handbooks.
SOP & training-doc retrieval
Field teams pull the current SOP, checklist, or training doc instantly.
Product & support knowledge
Let customers and agents find accurate answers straight from product manuals and tickets.
Support-ticket deflect
Resolve routine questions before they reach your team, grounded in your corpus.
Internal Q&A
Tenured and new employees ask one assistant instead of hunting across drives and chats.
Why your team's knowledge is hard to use today
Company knowledge lives scattered across drives, wikis, manuals, and inboxes. Finding the right answer costs hours — and customers often get answers that are out of date.
Answers scattered everywhere
Policies, processes, and product details sit across documents, wikis, and chat — no single queryable source.
Slow onboarding
New hires spend weeks hunting for how things actually work instead of asking one trusted assistant.
Support does not scale
Routine questions repeat daily; a grounded corpus answers them instantly with a citation.
Policy lookups under pressure
Field and frontline teams need the current rule now — retrieval surfaces the up-to-date passage, not a stale copy.
Multilingual answers
Employees and customers get answers in their own language, generated from the same corpus.
Cited, verifiable answers
Every answer traces to its source passages, so claims can be checked instead of trusted.
START SMALL, EXPAND OVER TIME
Turn your team's knowledge into a queryable AI
Bring the one document set that would save the team the most hours. Hyppe’s RAG platform does the rest — ingestion, indexing, retrieval, and cited answers already run in production.
THE RAG STACK
The stack underneath a queryable knowledge base
Ingestion, embeddings, hybrid retrieval, and reranking — already built and running for Hyppe tenants.
Hyppe's RAG platform removes the rebuild
Ingestion, hybrid retrieval, and multilingual generation already run in production for Hyppe tenants. A corporate knowledge assistant starts from that infrastructure, not from an empty repository.
Building RAG in-house
Weeks or monthsEvery layer is a project of its own
Retrieval quality can't be judged until every layer below it exists.
From your documents to an answer
Ingestion to answer on infrastructure that already runs
Live platform underneath
Your documents, queryable
Chunking, embeddings, retrieval, and reranking are already built and running for production tenants — your team brings the knowledge, not the plumbing.
No vector-DB rebuild
Hybrid retrieval out of the box
Ingestion
Hybrid retrieval
Multilingual generation
Feedback & reindex
The RAG stack underneath
What the platform removes
From your documents to a queryable AI
Document sources
What comes out
Ingest
Documents are ingested, deduplicated, and chunked ready for retrieval.
EXAMPLE CORPORATE USES
Real ways a knowledge assistant gets used
Each one starts with one document set that removes the most repeated questions or searches in your company.
Internal policy assistant — employees ask about current rules and get the updated passage.
Customer support knowledge base — customers self-serve from product manuals and FAQs.
Sales enablement assistant — reps look up pricing, playbooks, and objection handling instantly.
Onboarding documentation assistant — new hires ask how policies and processes actually work.
AI-powered platform for Estetix
Estetix shows what Hyppe can build for a specialized business: AI-powered product development, RAG-based knowledge systems, automated intake flows, lead qualification, customer notifications, and business process automation.
Visual context and inquiry intent are analyzed into structured data
Qualified intake with matching treatment logic
Ready to turn your knowledge into a queryable AI
Bring the one document set that would save your team the most hours. Hyppe ingests it and answers with citations — already running in production.
Talk to us about your document volume