Solutions
AI Knowledge Base & Enterprise Search
Answers exist somewhere in your wikis, drives, tickets and chats, but nobody can find them quickly.
In one paragraph
An AI knowledge base uses retrieval-augmented generation (RAG) to index your documents, wikis, tickets and messages, then answers employee questions in plain language with citations to the source. Permissions from the source systems are respected, so people only see what they are allowed to see. AIYatch builds the ingestion pipeline, vector search, assistant and evaluation set, and connects it to Slack, Teams or your intranet.
What you get
- Faster answers for employees, with the source one click away
- Fewer repeated questions to experts and support teams
- Access controls preserved from your existing systems
- Insight into what people ask and where documentation is missing
Services involved
Frequently asked
Enterprise search with RAG understands meaning rather than just keywords, combines results from many sources and returns a synthesised answer with citations instead of a list of links. It also handles follow-up questions in conversation. Keyword search remains part of the system for precision, and permissions from the source systems are enforced on every query, so the experience is both smarter and as safe as your existing tools.
Connectors re-index sources on a schedule or via webhooks, and deleted or restricted documents are removed from the index. We monitor unanswered questions so content owners can fill gaps, and evaluation sets catch quality regressions when content changes. Freshness intervals are set per source, so fast-moving tickets update more often than policy documents.
Related work
Outcomes, not demos.
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