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What is Ovrin?

Ovrin is a cloud-based computing platform specifically designed for developers engaged in creating AI agents and software that need to run in controlled environments. The platform allows users to utilize a REST API, Python, and TypeScript SDKs or an MCP server to create temporary Linux sandboxes, execute shell commands, manage stateful code, handle files, configure scoped API keys, and retrieve execution results. It also includes prebuilt configurations like Claude Code, OpenAI Codex, Gemini CLI, and DeepSeek Harness, while offering browser workflows that work seamlessly with Chrome and Playwright. Furthermore, Ovrin incorporates features such as persistent memory, lifecycle controls for sandboxes, usage analytics, and concurrency limitations. Typical use cases for Ovrin involve running coding agents, automating browser-based tasks, and executing code produced by various models. Importantly, the platform provides a free tier, with multiple paid plans available that enhance concurrency and compute costs based on usage. In essence, Ovrin is designed to facilitate and optimize the development of AI solutions by delivering a dynamic and adaptable environment for developers. Additionally, its user-friendly interface and comprehensive features make it an appealing option for both novice and experienced programmers alike.

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.

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Integrations Supported

Model Context Protocol (MCP)
Claude
Cursor
Gemini CLI
OpenAI Codex
Visual Studio Code

Integrations Supported

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

API Availability

Has API

API Availability

Pricing Information

$19/month
The Developer plan costs $19 per month plus metered compute charges based on vCPU and memory usage. The free tier includes a limited sandbox allowance and concurrency. Paid plans include higher concurrency and additional usage options.
Free Version

Pricing Information

Free
Free Version

Supported Platforms

SaaS

Supported Platforms

On-Prem

Customer Service / Support

Not specified

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Online Training

Company Facts

Company Location

United States

Company Website

www.ovrin.app/

Company Facts

Organization Name

Archestra

Company Location

United States

Company Website

archestra.ai/

Categories and Features

Categories and Features

Agentic AI

Not specified

AI Infrastructure

Not specified

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