Full documentation: deploy.sympozium.ai/docs
Quick Install (macOS / Linux)
Homebrew:
brew tap sympozium-ai/sympozium
brew install sympozium
Shell installer:
curl -fsSL https://deploy.sympozium.ai/install.sh | sh
Then deploy to your cluster and activate your first agents:
sympozium install # deploys CRDs, controllers, and built-in PersonaPacks
sympozium # launch the TUI — go to Personas tab, press Enter to onboard
sympozium serve # open the web dashboard (port-forwards to the in-cluster UI)
Advanced: Helm Chart
Prerequisites: cert-manager (for webhook TLS):
kubectl apply -f https://github.com/cert-manager/cert-manager/releases/download/v1.17.1/cert-manager.yaml
Deploy the Sympozium control plane:
helm repo add sympozium https://deploy.sympozium.ai/charts
helm repo update
helm install sympozium sympozium/sympozium
See charts/sympozium/values.yaml for configuration options.
Why Sympozium?
Sympozium serves two powerful use cases on one Kubernetes-native platform:
- Orchestrate fleets of AI agents — customer support, code review, data pipelines, or any domain-specific workflow. Each agent gets its own pod, RBAC, and network policy with proper tenant isolation.
- Administer the cluster itself agentically — point agents inward to diagnose failures, scale deployments, triage alerts, and remediate issues, all with Kubernetes-native isolation, RBAC, and audit trails.
Key Features
| PersonaPacks | Helm-like bundles for AI agents — activate a pack and the controller stamps out a full agent team |
| Skill Sidecars | Every skill runs in its own sidecar with ephemeral least-privilege RBAC, garbage-collected on completion |
| Multi-Channel | Telegram, Slack, Discord, WhatsApp — each channel is a dedicated Deployment backed by NATS JetStream |
| Persistent Memory | SQLite + FTS5 on a PersistentVolume — memories survive across ephemeral pod runs |
| Scheduled Heartbeats | Cron-based recurring agent runs for health checks, alert triage, and resource right-sizing |
| Agent Sandbox | Kernel-level isolation via kubernetes-sigs/agent-sandbox — gVisor or Kata with warm pools for instant starts |
| MCP Servers | External tool providers via Model Context Protocol with auto-discovery and allow/deny filtering |
| TUI & Web UI | Terminal and browser dashboards, or skip the UI entirely with Helm and kubectl |
| Any AI Provider | OpenAI, Anthropic, Azure, Ollama, or any compatible endpoint — no vendor lock-in |
Documentation
Development
make test # run tests
make lint # run linter
make manifests # generate CRD manifests
make run # run controller locally (needs kubeconfig)
License
Apache License 2.0