Teams

Enable teams of users in your company to securely access AI apps in your organisation

How does it work

Agent Cloud is designed to work within an enterprise with a data model, which includes Organisation > Team > User setup.

Users can be added into teams which are isolated in the data access that they have.

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Get started with
Teams
Invite hundreds of users securely to the platform
Ensure users can't access too much data
Segment access by creating teams
Get started

Explore other features

Explore

Security

Ensure LLM chat apps don't share more data than they should

Knowledge Retrieval (RAG)

Enable advanced RAG pipelines, letting you split, chunk, embed and retrieve knowledge from over 300 data sources

Open Source or Cloud LLMs

You can bring your own Open AI key or use one of 10 cloud hosted models (LLAMA2, Mistral 7B, Hugging Face). Agent Cloud Open Source users can also connect to their own Open AI compatible endpoints.
Build a RAG Chat to Bigquery data
Watch showreel

The end to end RAG pipeline

Select your connector

Use our collection of data sources to sync data from other systems like confluence or upload your own pdf, docx, txt or csv file.
When selecting systems like databases (postgres, snowflake, bigquery) you can select tables and even columns to ingest.

Prep your data

For files you can provide instructions on how to split and chunk your data. Leverage Open AI latest text-embedding-3 for embedding or select from open source models like BGE/base.

Vector store your data

Once data has been embedded the platform will store your data within a vector database. We also expose

Keep data fresh

Select what frequency you would like to sync data from the source. This can be manual, scheduled or a cron expression. This means users can query fresh data and know how recent the source was updated.

Start chatting with your data!

Now that data is synced, simply create an agent with your choice of LLM and start a session to talk to your data.

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