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What is Agent Cloud?

Agent Cloud enables companies to host their own AI App platform. (imagine a self hosted GPT builder platform with extra goodies) There are two types of apps you can build and deploy to your employees.

App Type Use Cases

Agent Cloud offers flexibility in app types, allowing for various use cases across industries.
Deploy conversational chat apps to handle customer inquiries and support tickets efficiently.
Create process apps to automate internal workflows, such as employee onboarding or document approval processes.
Utilize conversational chat apps to analyze and query data from multiple sources, empowering teams to make data-driven decisions.
Deploy Agent Cloud entirely on-premises or within a private cloud environment to ensure maximum control over data privacy and sovereignty. This deployment option is ideal for organizations with strict regulatory requirements or sensitive data handling policies.
Create interactive learning experiences using conversational chat apps powered by Agent Cloud. Educators can leverage AI to deliver personalized tutoring, simulate real-world scenarios, and facilitate collaborative learning environments.
Implement AI-driven solutions in the financial services sector to enhance customer service, automate routine tasks, and mitigate risks. Agent Cloud can power chatbots for banking inquiries, fraud detection algorithms, and personalized financial advisory services, improving operational efficiency and customer satisfaction.
Develop AI-powered healthcare applications to streamline patient care, medical diagnostics, and administrative processes. Agent Cloud can support virtual healthcare assistants, medical chatbots, and remote patient monitoring systems, improving access to healthcare services and optimizing workflows for healthcare providers.

App Ecosystem Architecture Overview

Diagram of the functional structure of the app showing connections between teams, users, permissions, and system components in Agent Cloud

Organizational and Functional Map

Building Blocks of Our Chat Ecosystem

In order to build an end to end scalable platform that empowers companies to deploy fully private LLM chat apps for their employees, the application must be self hostable and able to use open source embeddings and LLMs. To mitigate hallucination, companies also need scalable RAG. So we decided to power the end-to-end creation of these two apps. This includes:
  1. RAG as a Service which comes which enables you to sync and embed data from hundreds of data sources with a built in vector DB. To accomplish this we have abrstacted away both Airbyte (ELT) and Qdrant (Vector DB)
End to End RAG-a-a-S by Agent Cloud
  1. Multi agent engine which enables you to create tasks and assign them to a group of agents. To accomplish this we have abrstacted a langchain based multi agent runtime called crewai.
Augmented Human/AI teams

Augmented Human/AI teams

Augmented Human/AI tasks

Augmented Human/AI tasks

Imagine having your own Open AI GPT builder platform

Except with 4 key differences:
  1. Self host it on your companies cloud (keeping your data secure) - for open source users only
  2. Connect to any LLM (Ollama, LM Studio, Open AI, Azure Open AI - with more coming)
  3. Create RAG chat apps that retrieve knowledge from than just files, and can sync data from hundreds of datasources
  4. Create multi agent apps that can help you automate manual processes

Managed version

Sign up to our cloud version here

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  2. Latest Product Updates? See Changelog