Fully private AI agent workforce running entirely on your hardware. No data leaves your device. No API costs. No cloud dependency.
Some organizations can't send data to the cloud. Legal, compliance, competitive sensitivity, or simple preference — the reasons vary, but the requirement is absolute: nothing leaves the building.
Organized Teams — Local gives you the same structured agent workforce as the Cloud deployment, but running entirely on hardware you own and control. Open-weight models replace frontier APIs. Local inference replaces cloud calls. Your data stays on your device.
Same Slack experience as Cloud. Send a message, get work done. The bot token connects your Slack workspace to the local agent — messages flow in, responses flow out. The processing happens entirely on your machine.
Open-source coding agents that connect to local models instead of cloud APIs. Same back-and-forth chat interface through Slack. Same ability to read code, make changes, run commands, and respond with results. Different engine underneath — one that never phones home.
The inference backbone. Qwen-Agent provides a three-level architecture: atomic components (models + tools), high-level agents, and application-layer assistants. Native MCP integration connects your agents to local tools. The built-in code interpreter runs in a sandboxed Docker container. RAG handles document processing for 1M+ token contexts.
Browser automation via BrowserQwen lets agents interact with web interfaces when needed — still running through local models, still keeping data on-device.
Choose from the leading open-weight model families: Qwen (Alibaba), Llama (Meta), Mistral, or any model compatible with your hardware. M-series Apple Silicon handles inference efficiently — an M3 Mac Mini runs Qwen-2.5-72B at usable speeds for agent tasks. No per-token billing. No API rate limits. No usage caps.
Same organizational structure as Cloud. Org charts define agent hierarchies. Goals cascade from mission to task. Budgets track compute usage (local resource allocation instead of token costs). The ticket system maintains full audit trails. Self-hosted with embedded Postgres — no external database dependency.
FrawdBot runs locally alongside your agents. Same 12 behavioral rules, same rolling statistical baselines, same campaign detection — but all analysis happens on your hardware. Agent activity patterns are monitored without any data leaving the device. Insider threat detection that respects the same privacy guarantees as the rest of the stack.
Local instance of the management dashboard. Monitor agent activity, review task queues, adjust resource allocation, and manage the agent fleet — all through a browser interface running on localhost. No cloud dashboard, no external telemetry.
PostHog runs self-hosted alongside your agent fleet — same product analytics, session replay, and feature flags as the Cloud deployment, but entirely on your hardware. Track agent usage patterns, task completion rates, and feature adoption without any data leaving the device. HogAI natural language queries work against your local ClickHouse instance.
Event data stays in your local PostgreSQL and ClickHouse databases. No external telemetry. No cloud analytics. Complete analytical sovereignty matching your data sovereignty.
Full OTEL-based observability running locally. Claude Code Hooks (or OpenCode equivalents) emit spans to a local OTEL Collector. Prometheus captures infrastructure metrics. Grafana dashboards visualize token usage, task completion rates, model routing decisions, and resource utilization — all on localhost.
Langfuse runs self-hosted for LLM trace exploration, prompt management, and evaluation scoring. FrawdBot monitors all agent activity patterns locally. No telemetry leaves the device. The same seven metric namespaces available in the Cloud deployment run entirely on your hardware.
Read the full Observability Architecture paper →