From your first agent to production scale
RooAGI is focused on one problem: making AI agents reliable and deployable in the real world. We build the infrastructure that supports the entire agent lifecycle — from memory and development to execution, private model hosting, and tool connectivity. Our five products are different components of that unified platform.
- ● Remember
- ● Build
- ● Run
- ● Serve
- ● Connect
Remember. Build. Run. Serve. Connect.
One stack for running agents in production
Three tools to start from, and two that connect them together.
Lint-AI, AgentFlow, and Mogg run entirely on your own hardware — local by default for the MCP Server too.
Remember
Open source · GitHubLint-AI
Lint for AI-generated knowledge
Retrieval-grade memory for coding agents, plus corpus linting that flags orphaned pages and missing cross-references across your docs.
- Recall@5
- 86.9%
- Query latency
- 5.1ms
- GPU required
- No
Build
SaaS, HostedAgent Builder
Build AI agents in minutes, not months
A visual, no-code builder for production agents — pre-built agents to start from, or design your own with drag-and-drop tools.
- Tool integrations
- 10+
- Code required
- None
- Avg. build time
- 5 min
Serve
Contact UsMogg
A native CUDA runtime for in-house model serving
Hand-tuned CUDA kernels and KV caching for in-house inference, for teams who want models running on their own hardware.
- Models
- LLaMA, Qwen, Muse Glimmer
- Precision
- FP16 / BF16
- Status
- In development
AgentFlow is the engine behind Agent Builder; the MCP Server is how outside tools plug into all of them.
Run
GitHub releasesAgentFlow
The execution runtime for agent graphs
Fault-tolerant execution, working memory, and MCP-native tool orchestration for agent work that runs longer than a single prompt. Powers Agent Builder.
- Python support
- 3.10–3.13
- Platforms
- 2
- LLM providers
- 5+
Connect
Direct downloadMCP Server
Agent tooling over the Model Context Protocol
Exposes your tools to any MCP-speaking agent over SSE, WebSocket, or stdio — with zero per-tool boilerplate to write.
- Tools exposed
- 76
- Setup
- 3 lines
- Per-tool overhead
- 0
Let's talk about your agents
Whether it's agent memory, a no-code build, or in-house model serving, tell us what you're working on and we'll point you to the right place to start.
Free Architecture Review
We'll look at your current agent setup and flag where memory, tooling, or serving is the bottleneck
Custom Deployment Guidance
Tailored recommendations for your use case, team size, and hardware
Enterprise Support Options
24/7 support, priority updates, and dedicated engineering resources
Built for teams running agents in production
From open-source Lint-AI users to enterprises deploying custom inference — RooAGI covers the whole stack.