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OpenMake
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About OpenMake
OpenMake is a self-hosted platform that turns open-weight AI models into a governed system inside an organization’s own infrastructure. It provides an agent runtime and a control plane that lets administrators select models, connect private data, and define what agents are permitted to do without relying on external services. The platform supports research agents that search internal documents, ground answers in those sources, verify claims, and produce reports while maintaining a full audit trail. It can operate in private clouds, on-premise environments, or air-gapped networks, and is designed for organizations that require data and model ownership. OpenMake uses a replaceable model gateway so models like Qwen, EXAONE, Llama, or Mistral can be swapped without changing the orchestration layer. Agent tasks, tools, and artifacts are executed in separate boundaries, allowing granular permissions and sandboxing. The system also supports checkpointing, enabling tasks to resume after server restarts.
Key features
- Agent orchestration with multi-step task delegation
- Private data retrieval and grounding in internal documents
- MCP tool integration with administrator-approved servers
- Artifact generation including reports, code, tables, and images
- Administrator-defined approval policies and human gate checks
- Model gateway supporting Qwen, EXAONE, Llama, Mistral, and OpenAI-compatible endpoints
- Sandboxed execution environment for agent tasks
- Audit logging of all agent actions and resource usage
Use cases
- Internal research and document analysis without external data exposure
- Private knowledge base Q&A with verifiable citations
- Automated report generation from sensitive organizational data
Pros
- Self-hosted deployment in private cloud, on-premise, or air-gapped environments
- Replaceable open-weight models with no vendor lock-in
- Granular control over agent permissions, policies, and sandboxing
- Full audit trail of agent actions, files accessed, and outputs produced
- Checkpointing for task recovery after server restarts
Cons
- Requires self-hosting infrastructure or private cloud setup
- No indication of cloud-hosted managed service availability
- Limited to open-weight models and OpenAI-compatible endpoints
Frequently asked questions about OpenMake
What is OpenMake?
OpenMake is a self-hosted platform that transforms open-weight AI models into a governed system within an organization's infrastructure. It provides an agent runtime and control plane for administrators to select models, connect private data, and define agent permissions without relying on external services.
Who should use OpenMake?
OpenMake is designed for organizations that require full data and model ownership, such as enterprises, research institutions, or government agencies operating in private clouds, on-premise environments, or air-gapped networks.
How does OpenMake handle model selection?
OpenMake uses a replaceable model gateway, allowing organizations to swap models like Qwen, EXAONE, Llama, or Mistral without altering the orchestration layer, ensuring flexibility in model choices.
Can OpenMake integrate with private data sources?
Yes, OpenMake connects private data sources to ground agent responses in internal documents, enabling research agents to search, verify claims, and produce reports while maintaining an audit trail.
Does OpenMake support offline or air-gapped environments?
Yes, OpenMake is designed to operate in private clouds, on-premise environments, or air-gapped networks, making it suitable for organizations with strict data isolation requirements.
How does OpenMake ensure security and governance?
OpenMake enforces granular permissions and sandboxing by executing agent tasks, tools, and artifacts in separate boundaries, while also supporting checkpointing to resume tasks after server restarts.
