Open-Source AI Agents for Enterprise Work: Platforms You Can Actually Deploy (2026)

Key Takeaways

• AI agent platforms help businesses deploy AI for employee use.
• Frameworks help developers build and customize AI agents.
• Open source licenses define how companies can use and modify software.
• Omni and Onyx focus on enterprise search and AI agents.
• OpenWork focuses on AI workspaces for files and tasks.
• LibreChat and Open WebUI focus on self hosted AI interfaces.
• Self hosting gives companies more control over data and infrastructure.
• Teams must check licenses, permissions, connectors and server requirements before deployment.

AI agents are moving beyond simple chatbots. Businesses are using them on a large extent which include:

• search internal knowledge
• analyse company information
• work across business applications
• complete tasks using the context employees already have access to.

But choosing an AI agent for enterprise use is different from choosing a developer framework. A framework helps engineers build an agent. A platform gives a company a more complete system that employees can use after deployment. This guide focuses on open source AI agent platforms that businesses can deploy and self-host. It covers options that give businesses greater control over their data, models, and infrastructure. It is used to compare:-

• Licensing
• Permissions
• Connectors
• deployment requirements

and hosted options so you can see what each platform actually offers before putting it into production.

Open source AI agent platforms vs frameworks: which are you shopping for?

Before comparing products, it helps to separate AI agent frameworks from AI agent platforms.

An AI agent framework is primarily a developer toolkit. It gives engineers the components needed to build an agent. It connects models and tools, defines workflows, and controls how the agent behaves. The company still needs to build the application around those components.

For example LangGraph is an MIT-licensed open-source framework. It is used for building agent applications. CrewAI is another developer-focused framework for orchestrating AI agents and workflows.

An AI agent platform sits at a different level.

Instead of building the whole user experience from a framework, you can use a platform that already provides the main components. It can provide:

• The agent runtime
• The user interface
• Authentication
• Company data connections
• Data retrieval
• Permission controls
• Deployment tools

This can save the company from building each part separately. Platforms such as Omni and Onyx are closer to this category. Omni is positioned as an open-source, self-hosted AI agent for company-wide work. Onyx combines enterprise search, AI chat, agents, RAG and connectors in one platform.

The practical difference

Build an agent from scratch? Use a framework for more control. Deploy an AI agent for employees? Use a platform for faster setup. Simply put: “How do I build?” → Framework. “How do I deploy?” → Platform.

What “open source” actually means here: a license check

“Open source” does not simply mean a company’s code is available online. The software license defines how you can use that code. For enterprises, check whether you can:

• Deploy it internally
• Modify the software
• Run it on your own infrastructure
• Redistribute modified versions
• Use it commercially

Also check whether any enterprise features have a separate license.

MIT

The MIT license is a permissive open source license. It allows organisations to use, modify, distribute and commercially use software. They must retain the required copyright and license notices. LangGraph and LibreChat are both MIT licensed.

Apache 2.0

Apache 2.0 is also a permissive open source license. It allows commercial use, modification and distribution. It also includes specific patent rights. Omni’s complete public repository is licensed under Apache 2.0.

Open Source vs Source Available vs Fair Code

A project can publish its source code without being truly open source. The license may still include restrictions on commercial use, redistribution or branding. For this article, license and product information was checked against official sources in September 2026

Licensing models at a glance

The best open source AI agent platforms for enterprise, compared

The platforms below are compared on:

• License
• Free or open source features
• Permission controls
• Connectors
• Self hosting
• Infrastructure requirements
• Hosted availability
• One practical limitation

The products also serve different purposes.

• Omni and Onyx: Enterprise search and AI agent platforms.
• OpenWork: AI workspaces and agents for employee machines.
• LibreChat and Open WebUI: AI interfaces that connect users to different models and tools.

Omni: the open-source AI agent with permissions in the free version

Omni is a self hosted AI agent for company work. It connects workplace applications and gathers company context. It can analyse information and perform supported actions.

License

Omni’s public repository is licensed under Apache License 2.0. The repository states that the complete product in the public repository is covered by this license.

Permission-aware company context

Omni supports permission aware retrieval. It can inherit permissions from connected systems. Users can access company information. This is based on the permissions they already have in the original system.

Workplace integrations

As an open source AI agent with connectors for popular workplace tools, Omni supports integrations with:

• Google Workspace
• Microsoft 365
• Slack
• Jira
• Confluence
• HubSpot
• GitHub
• ClickUp
• Linear.

It also supports custom integrations through MCP and connector SDKs.

Deployment

Omni is designed for self hosting. It supports Docker Compose for single server deployments. For production, it also supports Terraform deployments on AWS and GCP.

Models

Omni supports models from:-

• Anthropic
• OpenAI
• Gemini
• AWS Bedrock
• Vertex AI
• Azure AI Foundry.

It also supports OpenAI compatible endpoints. For local inference, it can work with vLLM, Ollama and LM Studio.

Practical limitation

Omni is self hosted software. The organisation is responsible for its infrastructure and security. It must also configure integrations and maintain the environment. Alternatively, it can choose the managed cloud option.

Hosted option

Omni will also soon offer Omni Cloud, a managed version, where we will handle hosting, updates, security and scaling. The self hosted community version is available for free. Paid plans add enterprise controls and support. Want to evaluate Omni? Start with the official repository and deployment documentation. You can also request a demo through Omni’s official site.

Onyx: enterprise search, RAG and agents in one platform

Onyx is an open-source AI platform combining enterprise search, RAG, AI chat, agents and actions. It is designed to connect company knowledge sources. It is used to provide permission-aware answers across them.

License

Onyx Community Edition is available under the MIT license. However, the repository separately licenses content inside its ee directories under the Onyx Enterprise License. That distinction matters when evaluating which enterprise features are available under the open-source edition.

Permissions

Onyx supports permission-aware retrieval. But its current commercial positioning places some advanced permission functionality in Enterprise. The official pricing page lists Permission Inheritance among Enterprise features.

Connectors

Onyx currently advertises 40+ connectors, including tools such as:-

• Slack
• Gmail
• Google Drive and
• GitHub.

Its connector system continuously indexes connected sources. It can enforce permissions where the relevant feature is available.

Deployment

Onyx can be self-hosted using Docker Compose. It also supports Kubernetes and Helm based deployment. Its standard architecture is more involved than a simple chat interface. It is because it includes components for indexing, search, background jobs and storage.

Server requirements

The current official infrastructure calculator recommends

• 16 vCPUs
• 96 GB RAM
• and 1 TB disk for its production configuration.

Hosted option

Onyx also provides a cloud offering. Its current pricing page lists a Business plan at $20 per user per month with annual billing. It also has an Enterprise plan with additional deployment and support options.

Practical limitation

Onyx’s full deployment has a larger infrastructure footprint than lightweight AI chat interfaces. Teams should account for search, indexing and supporting services when estimating operational requirements.

OpenWork: an AI workspace for files and knowledge work

OpenWork takes a different approach from platforms like Omni and Onyx. It is a desktop AI workspace for macOS, Windows and Linux. Users can work with AI agents on their own files. It supports multiple model providers instead of one model vendor.

License and free offering

OpenWork’s desktop app is open source under the MIT license and is free for any use, with no user cap. Its organisational control plane, OpenWork Den, is source available and offers a free tier for up to five users. The free tier supports self hosting and lets organisations use their own model keys Paid Team and Enterprise plans add features such as organisation management, SSO, SCIM and white labelling.

Permissions and deployment

OpenWork is more local first than a traditional enterprise search platform. Its self hosted setup keeps source code and prompts within the organisation’s infrastructure. Users can connect to the LLM provider of their choice.

Connectors and extensibility

OpenWork supports skills, MCP servers and plugins. Teams can package configurations and skills for other employees. Employees can then import them into their own workspaces.

Server requirements

OpenWork is a desktop application, so its infrastructure needs differ from enterprise search platforms. The exact requirements depend on the deployment model.

Practical limitation

OpenWork is not a direct replacement for enterprise search platforms. It is an AI work environment for employees working with files, tools and agents.

LibreChat: a flexible self-hosted AI interface

• LibreChat is mainly a multi provider AI chat interface.
• It is different from enterprise knowledge platforms like Omni and Onyx.
• It gives organisations a self hosted interface for different AI providers and models.
• It also supports features such as MCP and other integrations.

License

LibreChat’s application is licensed under the MIT license.

Deployment

LibreChat can be installed using Docker, npm or Helm. Its Docker Compose setup can also run dependencies such as MongoDB, MeiliSearch, the RAG API and a vector database.

Practical limitation

LibreChat provides a flexible AI interface. Companies seeking deeply integrated enterprise search may need extra configuration and infrastructure. It is therefore a different category of tool from Omni and Onyx.

Open WebUI: ChatGPT-style self-hosted AI interface

• Open WebUI is a self hosted AI platform.
• It provides a user-friendly interface for different models.
• It supports Ollama and OpenAI compatible APIs.
• It can run entirely within an organisation’s infrastructure.

License

Open WebUI requires careful license review. From v0.6.6 onwards, its license includes a branding protection clause. The project says this newer license is not OSI approved. However, it still allows use, modification and self hosting under its stated conditions.

Deployment

Docker is the recommended installation method for most users. Kubernetes is also available for enterprise deployments

Enterprise controls

Open WebUI supports features such as SSO, LDAP and RBAC. It also supports on premises and air gapped deployments.

Practical limitation

It is mainly an AI interface, not a complete enterprise search platform. Organisations needing extensive source system indexing and inherited document permissions should check whether its connectors and retrieval model meet their needs.

Self-hosted AI assistant options if you’re coming from Glean or Moveworks

A move from a closed enterprise AI platform to a self hosted system changes the setup. The organisation gets more control over its infrastructure.

What self hosting gives you

With self hosting, organisations can:

• Choose cloud or on premises infrastructure
• Select which models process company data
• Control network boundaries and data residency
• Inspect and modify the software
• Manage backups and data retention

What your team needs to manage

Self hosting also adds operational responsibilities, including:

• Infrastructure
• Databases and storage
• Updates and security patches
• Authentication
• Backups and monitoring
• Connector credentials
• Disaster recovery
• Model and API configuration

The exact requirements depend on the platform. A lightweight AI interface may need much less infrastructure than an enterprise search system indexing millions of documents.

Which platforms fit this use case?

For companies looking for open source alternatives to Glean, Omni and Onyx are relevant options. Both combine company search with AI functionality and self hosting.

Open-source AI agents compared: license, free version, and server needs

The following table reflects information checked against official product sources in September 2026.

How to choose and test an open source AI agent

Choosing a platform should start with the company’s actual deployment requirements rather than the number of features listed on a product page.

1. Check the actual software license

Do not rely only on a GitHub repository labelled “open source”. Check the software license. Review its rules for commercial use, modification and redistribution. Also check enterprise features, branding requirements and separate enterprise modules.

2. Check the free version

Check exactly what the community edition includes. A product may have an open source core. However, features such as SSO, audit logs, permission inheritance and SCIM may require a commercial license.

3. Test permission handling

Create two test users with different access rights. Give User A access to a document that User B cannot access. Ask the same question to the agent as both users. Check that User B cannot access User A’s restricted information.

4. Check your required connectors

List the systems employees actually use, such as

• Google Drive
• Gmail, Slack
• Microsoft 365
• SharePoint
• Jira
• Confluence
• GitHub
• CRM
• internal databases.

Check whether the platform has a supported connector for each system. Do not assume an integration exists just because the platform supports MCP

5. Check infrastructure

Do not size the server based only on the AI interface. Enterprise search may also need storage, indexing services, databases, queues and retrieval infrastructure.

6. Test with real company documents

Use realistic information during the trial. Test questions about internal policies, project decisions, Jira issues and company reports. Check accuracy, citations, permissions, connectors, agent actions and reliability. A Docker based trial can also help. It shows the team the deployment effort before a larger infrastructure setup.

FAQs

What is an open source AI agent platform?

An open source AI agent platform provides a deployable environment for AI agents. Its source code is available under an open source license. Unlike a developer framework such as LangGraph, it can include:-

• a user interface
• model connections
• company data retrieval
• integrations and deployment tools.

These features help organisations provide employees with an AI system they can use.

What is the best open source alternative to Glean?

The right alternative depends on what you need from Glean. Omni focuses on self hosted AI agents for company wide use. It also provides permission aware company context. Onyx combines enterprise search, RAG, AI chat and agents. It supports more than 40 connectors. LibreChat and Open WebUI focus more on self hosted AI interfaces. They are not full enterprise search platforms.

Can I self-host an AI agent platform for free?

Some platforms can be self hosted without a software license fee. However, free software does not mean zero deployment cost. Your organisation may still pay for servers, storage, model API usage, backups and monitoring. Time of engineering also adds to the cost. Enterprise features may require a paid license.

Do open source AI agents support permission-aware access?

Permission handling varies by platform. Omni includes permission aware company context in its open source core. Onyx supports permission aware retrieval. However, its current product information lists permission inheritance as an Enterprise feature. Always test permissions against the actual source systems. Test the specific edition you plan to deploy.

What server do I need to self-host an AI agent?

Server requirements vary by platform and workload. Omni does not provide one universal minimum production specification in its public documentation. Onyx recommends 16 vCPUs, 96 GB RAM and 1 TB disk for production. Larger document volumes may need more resources. Lightweight platforms may need much less infrastructure.

Is Dify open source?

Dify publishes its source under a modified Apache License 2.0, not the unmodified Apache 2.0 license. Commercial use is allowed, but operating a multi-tenant service requires written authorization, and its frontend branding must be retained. Check Dify’s license for your intended use.

Is n8n open source?

n8n describes its source code as fair-code rather than open source. Its Sustainable Use License allows self-hosting and commercial use within certain conditions, but it is not an OSI-approved open source licence.