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Synthetic Brew
Open-source AI agent runtime — describe it in plain English
Open-source, self-hosted AI agent runtime. Describe what you need in plain English and it builds, deploys, and orchestrates the agents — wired to your tools, memory, and knowledge. Grounded with RAG + knowledge graphs. Any LLM, one Docker command, no lock-in.
Hey Product Hunt! 👋 I'm Tim, founder of Synthetic AI.
When we set out to put real AI into our IoT platform, the chat was the easy part. The hard part was everything underneath — the infrastructure that makes AI reliable on real-world data: retrieval, knowledge graphs, tools, memory, permissions, and a record of every action it takes.
That took us six months to build properly. And it turned out to be far bigger than a feature — big enough to be a product of its own. So we open-sourced all of it.
Synthetic Brew is a self-hosted AI agent runtime:
- Describe the agent you need in plain English — the AI Builder configures the agents, tools, memory, and workflows (and yes, the Builder itself runs on Synthetic Brew)
- Grounded with vector RAG + typed knowledge graphs, so it doesn't make things up
- MCP tools, multi-agent ReAct orchestration, REST API + SSE streaming, embeddable chat widget
- BYOK — OpenAI, Anthropic, Google, Groq, DeepSeek, or Ollama
- One Docker command, your infrastructure, your data. No lock-in, no per-token markup.
Honest license note: the Community Edition is BSL 1.1 (converts to Apache 2.0 after 4 years) — free forever to self-host, unlimited agents.
I'll be here all day — ask me anything about the architecture, the knowledge-graph approach, or the six months of mistakes we made so you don't have to.
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About Synthetic Brew on Product Hunt
“Open-source AI agent runtime — describe it in plain English”
Synthetic Brew was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #155 on the daily leaderboard. Open-source, self-hosted AI agent runtime. Describe what you need in plain English and it builds, deploys, and orchestrates the agents — wired to your tools, memory, and knowledge. Grounded with RAG + knowledge graphs. Any LLM, one Docker command, no lock-in.
Synthetic Brew was featured in Open Source (68.6k followers), Developer Tools (515.4k followers), Artificial Intelligence (473.1k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 218k products, making this a competitive space to launch in.
Who hunted Synthetic Brew?
Synthetic Brew was hunted by Tim Kravchunovsky. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Tim Kravchunovsky