Every serious AI team in Switzerland rebuilds the same stack — LLM gateway, vector search, agents, auth, monitoring, a data pipeline — under one hard constraint: the data cannot leave the building, so the convenient SaaS options are off the table. The Swiss AI Hub is the platform I architected and lead-developed at bbv to end that repetition. It is complete, self-hosted infrastructure for production AI — around 35 integrated containers behind one install command — and as of 2026 it is open-source under Apache 2.0, public at dev.ai-hub.bbv.ch and docs.ai-hub.bbv.ch.
The Hub wires best-of-breed open-source tools into one coherent stack and owns the integration between them:
One command brings the whole stack up via Docker Compose:
curl -fsSL https://raw.githubusercontent.com/bbvch-ai/aihub-core/main/install.sh | bash
Under five minutes later there is a running gateway, vector search, chat UI, auth, and monitoring, with eight pre-built agent types working immediately over an OpenAI-compatible REST API, WebSocket, MCP, and Slack/Teams. On top sits the Swiss AI Agent Protocol — typed event workflows over NATS/JetStream with human-in-the-loop escalation — and three SDKs (Agent, Pipeline, Process) so developers inherit auth, tracing, streaming UI, and cost tracking for free.
I am the architect and lead developer of the Swiss AI Hub. I designed the event-driven microservices architecture, led a team of five engineers, built the model-serving stack, defined the agent protocol and SDKs, and drove the strategy that turned it into a revenue-generating business area shipping across 15 projects for 12 Swiss enterprise clients. In 2026 I led its release as open-source under Apache 2.0.
Repository: github.com/bbvch-ai/aihub-core
Documentation: docs.ai-hub.bbv.ch
Overview: dev.ai-hub.bbv.ch
The Swiss AI Hub is a complete, self-hosted AI infrastructure platform: an LLM gateway, vector search, a multi-agent runtime, data pipelines, authentication, monitoring, and a chat interface, combined into one stack of around 35 containers. Organizations deploy and own the whole thing rather than subscribing to a SaaS or stitching together a code library. It runs on-premise, in a Swiss data center, or in any cloud, with no vendor lock-in.
Yes. As of 2026 the entire platform is open-source under the Apache 2.0 license. The code lives at github.com/bbvch-ai/aihub-core, the documentation at docs.ai-hub.bbv.ch, and a live overview at dev.ai-hub.bbv.ch. Any organization can deploy, inspect, and extend it without a licensing fee, and contribute back through an open pull-request process.
Joel Barmettler is the architect and lead developer of the Swiss AI Hub. He designed the event-driven microservices architecture, led a team of five engineers, built the model-serving stack and the three SDKs (Agent, Pipeline, Process), defined the Swiss AI Agent Protocol, and in 2026 led the platform's release as open-source under Apache 2.0.
The full stack — chat, embeddings, reranking, OCR, and speech — runs air-gapped on a single NVIDIA RTX 6000 Pro, with no external API dependency. It can also route to a Swiss LLM Cloud or scale across multiple GPUs without code changes.
One command installs everything via Docker Compose: LLM gateway, vector search, chat interface, authentication, and monitoring. A production deployment is up in under five minutes, with pre-built agents working immediately and no cloud provisioning required.
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