Knowledge base
One place for your agent to get all context from.
Your data sits in a dozen tools. A knowledge base puts it in one place, in a form an agent can search in a second.
Your agent cannot see any of your data.
- You explain your business to it every single time.
- It cannot see your email, files, customers or stock.
- So it guesses, you correct it, and you do it again tomorrow.
Storage, connectors, embeddings, retrieval.
Storage
One store
Everything you know, in one place instead of a dozen tools.
Integrations
Connectors
Pull in email, files, inventory and customer records as they change.
Vector embeddings
Meaning, not keywords
Text turned into numbers, so search finds what you meant, not what you typed.
Vectorisation model
The part that does the turning
Decides how well search understands you. Better model, better answers.
Retrieval, or RAG
Look it up, then answer
The agent fetches from your data first, then answers from that.
Live sync
Always current
Every email that arrives lands in the base, searchable, with nobody filing it.
Point it at the base once. It never asks again.
One line in the file your agent reads before every task.
From then on it looks up anything you have.
No briefing. No guessing.
Four lines, and every answer comes from your data.
## Company dataKnowledge base: kb.yourcompany.comSearch it before answering anything aboutorders, customers, stock or past emails.
A vector database is one piece of this.
Pinecone and the rest do that one job well. A knowledge base is the whole thing: store, connectors, model, retrieval, and the upkeep that keeps it true.
This is one of the things we build.
We work out what yours holds, build the base, and wire your agents into it.