Knowledge & RAG
Ground every answer in your own content. Mirakash builds knowledge bases with chunking, embeddings, and retrieval so an agent answers from your docs instead of guessing — sync content from connectors like Notion, and scope each knowledge base to the agents that should use it.
An agent that guesses is worse than no agent at all
A model with no grounding invents policy, quotes the wrong price, and contradicts your docs — confidently. Pasting knowledge into a prompt doesn't scale, goes stale the moment a doc changes, and blows past the context window.
The flow, end to end
Ingest
Add documents or sync from a connector like Notion; each source lands in a knowledge base.
Index
Content is chunked and embedded automatically so it's ready to retrieve.
Retrieve
At conversation time the agent pulls the most relevant chunks for the caller's question.
Answer
The agent responds from your content, grounded — not from the model's guess.
What's in the box
Knowledge bases
Create knowledge bases from your documents, scoped per workspace and per agent.
Chunking & embeddings
Content is chunked and embedded automatically so it's retrievable at conversation time.
Retrieval (RAG)
The agent retrieves the most relevant chunks per turn and answers from them, with the source in reach.
Connector sync
Sync knowledge from connectors like Notion; a re-sync keeps the base current as docs change.
Per-agent scope
Attach a knowledge base to the agents that should use it — nothing bleeds across scope.
Documents are the single grounding surface — chunked, embedded, retrieved
Rather than stuffing a prompt, knowledge is native: ingested from files or connectors, chunked and embedded on the way in, and retrieved per turn at conversation time. Keeping a base current is just a re-sync away.
- ✓Automatic chunking and embeddings on ingest
- ✓Per-turn retrieval scoped to the agent's knowledge
- ✓Connector sync re-indexes, no manual re-upload
Answers pinned to your content, scoped per agent
Each knowledge base is chunked, embedded, and attached to exactly the agents that should use it. At conversation time the agent retrieves the most relevant chunks for the question and answers from them, so responses track your docs — and a re-sync from Notion keeps them current.
- ✓Knowledge bases scoped per workspace and per agent
- ✓Notion connector sync keeps content current
- ✓Retrieval respects scope — it never widens visibility
Agent builder
Design a voice or chat agent with no code — persona, voice, knowledge, tools — and test it live in the browser.
Learn moreWorkflows & automation
An event-driven, node-graph engine that turns any signal into the right action, automatically.
Learn moreOmnichannel & web chat
One agent across phone, WhatsApp, SMS, email, and an embeddable, white-labeled web chat on your domain.
Learn moreReady to put an AI agent on every call?
Book a walkthrough and see the voice pipeline, telephony, workflows, QA, and human handoff working together — on one platform.