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What is Archestra?

Archestra is an open-source, self-hosted AI platform that facilitates the management and deployment of agents across an organization. It boasts agentic chat capabilities designed for users without a technical background, in addition to various applications, skills, collaborative initiatives, a server-side agent runtime, MCP orchestration, permission-aware RAG, LLM and MCP proxies, security safeguards, and extensive observability, all seamlessly integrated into one platform. Through single sign-on (SSO) authentication, users can engage with tools while maintaining their unique identities rather than relying on shared service accounts. The platform organizes projects to bring together chats, files, scheduled tasks, and instructions, while agents function within isolated containers, activated by triggers such as schedules, emails, or webhooks. MCP servers are deployed within the organization's Kubernetes environment, adhering to security-validated promotion protocols that implement separate credentials and network rules. Additionally, the knowledge bases can connect with Confluence, Jira, drives, and internal documents, preserving source-system ACLs to ensure users only access information they are authorized to view. Overall, this extensive array of features establishes Archestra as an essential asset for organizations aiming to enhance their AI deployment efficiency and governance. By offering a user-friendly experience coupled with robust security measures, Archestra empowers teams to innovate while maintaining stringent access controls.

What is Agent Substrate?

Agent Substrate is an open-source runtime that enables the creation and management of isolated, stateful agent and code-execution sandboxes tailored for Kubernetes ecosystems. It efficiently oversees the lifecycle of actors and workers, directing active workloads to a shared pool of resources, and can pause inactive sandboxes while preserving their memory and filesystem states for later utilization. By leveraging gVisor or Cloud Hypervisor microVMs for enhanced isolation, these sandboxes are equipped with distinct identity and networking controls for every actor. This platform is specifically designed for infrastructure and platform teams engaged in developing services for agent hosting, coding environments, and other activities that may involve untrusted or intermittent execution. The core framework is built to be portable across Kubernetes, with Google Cloud offering specialized deployment tools that are fine-tuned for GKE. Furthermore, users have the option to incorporate Filestore agent volumes to ensure that workspaces remain intact and retrievable throughout suspension and resumption cycles, thereby increasing the reliability of the development environment. By enabling such capabilities, Agent Substrate proves to be an indispensable resource for contemporary cloud-native applications, empowering teams to streamline their operations and maximize efficiency in managing complex workloads.

Media

Media

Integrations Supported

Model Context Protocol (MCP)
Anthropic
Azure OpenAI Service
Confluence
Gemini Enterprise Agent Platform
Jira
Kubernetes
OpenAI

Integrations Supported

Model Context Protocol (MCP)
Google Cloud Filestore
Google Cloud Platform

API Availability

API Availability

Has API

Pricing Information

Free
Free Version

Pricing Information

$0
Agent Substrate on GKE is offered at no extra charge. GKE pricing applies to the resources you create.
Free Version

Supported Platforms

On-Prem

Supported Platforms

On-Prem
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Archestra

Company Location

United States

Company Website

archestra.ai/

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

github.com/agent-substrate/substrate

Categories and Features

Agentic AI

Not specified

AI Infrastructure

Not specified

Categories and Features

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