Open source
AI App platform

Agent Cloud is building the open source equivalent of platform.openai.com and chat.openai.com so that both developers and consumers of AI Apps within any company can privately build and use AI within their company.
1

Private: Self host or use cloud

Agent Cloud is designed to be self hosted or
Self host instructions come with kubernetes helm files to deploy on your cloud
Cloud is perfect for companies that want to get up and running fast or don't want to manage infrastructure
2

Extensible: Bring your own LLM

We believe in the power open source to empower better use cases for companies
Use custom embedding models for RAG
Connect to local LLM models to optimise performance or reduce costs
3

Simple: Anyone can build and share AI apps in your company

We've created a no-code builder interface for anyone in the company to build and manage AI Apps whilst maintaining your security controls
Easily sync data for RAG use cases
Create agents inside the interface and share to Users, Teams or the entire Organisation

Overview of all the features

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.

Tools

Build custom tools/functions enabling your AI Agents to hit any 3rd party API service

Multi Agent Assistant (powered by Autogen)

Enable teams of LLM powered agents able to securely access your data and systems

Teams

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

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-small 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.

Build a RAG Chat to Bigquery data
Watch showreel

Privately chat to your data in your cloud.

Get started with Agent Cloud Community edition today or talk to us for enterprise enquiries.
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