gobii-platform

gobii-platform

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Gobii Platform is an open-source platform designed for running durable autonomous agents in production. Each agent can run continuously, wake from schedules and events, use real browsers, call external systems, and coordinate with other agents. It is optimized for reliable, secure, always-on agent operations for teams and businesses. Gobii treats agents as operational entities with addressable communication endpoints, allowing teams to contact them directly like AI coworkers. The platform provides security-first controls, encrypted-at-rest secrets, proxy-governed egress, and Kubernetes sandbox compute support. Gobii is purpose-built for secure, governed, always-on production execution in cloud or hybrid environments.

README:

Gobii fish mascot

Gobii Platform

Always-on AI employees for teams.
Built on browser-use. Designed for secure, cloud-native operations.

License Docker Compose Status

Website · Docs · Discord · Cloud

Gobii is the open-source platform for running durable autonomous agents in production. Each agent can run continuously, wake from schedules and events, use real browsers, call external systems, and coordinate with other agents. Each agent can also be contacted like an AI coworker: assign it an identity, email or text it, and it keeps working 24/7.

If you are optimizing for local-first personal assistant UX on a single device, there are excellent projects for that. Gobii is optimized for a different problem: reliable, secure, always-on agent operations for teams and businesses.


Gobii agent demo in action

Table of Contents

Why Teams Choose Gobii

  • Always-on by default: per-agent schedule state plus durable event processing.
  • Identity-bearing agents: each agent can have its own email address and SMS phone number, so teams can contact it directly.
  • Native agent-to-agent messaging: linked agents can coordinate directly.
  • Webhook-native integration model: inbound webhooks wake agents; outbound webhooks are first-class agent actions.
  • Based on browser-use: keeps /api/v1/tasks/browser-use/ compatibility while adding platform-level runtime controls.
  • SQLite-native operational memory: structured state substrate for long-running tool workflows.
  • Real browser operations: headed execution, persistent profile handling, and proxy-aware routing.
  • Security-first controls: encrypted-at-rest secrets, proxy-governed egress, and Kubernetes sandbox compute support.

Gobii vs OpenClaw (Production Lens)

OpenClaw is excellent software, especially for local-first personal assistant workflows and broad channel coverage. Gobii is optimized for a different target: cloud-native, secure, always-on agent operations for teams.

Dimension Gobii OpenClaw
Primary deployment model Cloud-native autonomous agent runtime (self-hosted or managed) Local-first gateway and personal assistant runtime
Always-on behavior Per-agent schedule + durable event queue continuity Heartbeat and cron/wakeup session patterns
Webhook model Inbound triggers plus outbound agent webhook actions in one lifecycle Strong gateway ingress hooks and wake/agent webhook routes
Channel strategy Fewer core channels with deeper lifecycle integration Wider channel surface with intentionally thinner per-channel depth
Agent identity Endpoint-addressable agent identities (email/SMS/web) Workspace/session identity model
Human interaction model Contact each agent directly through its own endpoint like an AI coworker Primarily session/workspace-oriented assistant interactions
Agent coordination Native agent-to-agent messaging Orchestrator/subagent flows
Memory substrate SQLite-native operational state Markdown-first memory with optional vector acceleration
Browser runtime Headed execution, persistent profiles, proxy-aware routing, distributed-worker friendly Headed execution, persistent local profiles, strong local operator UX
Security defaults Encrypted-at-rest secrets, proxy-governed egress, sandbox compute, Kubernetes/gVisor support Local-first by design, sandboxing available but deployment-dependent
Best fit Production team automation with governed runtime controls Personal/local assistant workflows and channel breadth

If your priority is secure, governed, always-on production execution in cloud or hybrid environments, Gobii is purpose-built for that.

AI Coworker Interaction Model

Gobii agents are designed to behave like AI coworkers, not disposable one-off tasks. You can email or text them directly, they wake from those events, execute work, and reply with context-aware follow-through.

sequenceDiagram
    participant U as You / Team
    participant E as Agent Email/SMS Endpoint
    participant Q as Per-Agent Event Queue
    participant A as Always-On Gobii Agent
    participant T as Browser/Tools/APIs

    U->>E: Send message to the agent
    E->>Q: Inbound event is queued
    Q->>A: Wake agent with full context
    A->>T: Execute tasks and gather outputs
    T-->>A: Results, files, and state updates
    A-->>U: Reply with outcome and next steps
    A->>Q: Stay active for follow-up events

How Gobii Works

flowchart LR
    A[External Triggers\nSMS · Email · Webhook · API] --> B[Per-Agent Durable Queue]
    C[Schedule / Cron] --> B
    B --> D[Persistent Agent Runtime]
    D --> E[Tools Layer]
    E --> E1[Browser Automation\nheaded + profile-aware]
    E --> E2[SQLite State\nstructured memory tables]
    E --> E3[Outbound Integrations\nwebhooks + HTTP]
    E --> E4[Agent-to-Agent\npeer messaging]
    D --> F[Comms Replies\nSMS · Email · Web]
    D --> G[Files + Reports + Artifacts]

Gobii Focus vs Typical Personal Assistant Stacks

Area Gobii focus
Runtime model Long-lived schedule + event lifecycle
Primary operator Teams and organizations
Agent identity Addressable communication endpoints
Orchestration Always-on processing + native A2A
Browser workload shape Production tasks with persisted state
Security posture Controlled egress, encrypted secrets, sandbox compute

Always-On Runtime: Schedule + Event Triggers

Gobii agents are built to stay active over time, not just respond in isolated turns.

sequenceDiagram
    participant S as Scheduler
    participant Q as Agent Event Queue
    participant R as Agent Runtime
    participant T as Tools
    participant C as Channels / Integrations

    S->>Q: enqueue cron trigger
    C->>Q: enqueue inbound event\n(email/sms/webhook/api)
    Q->>R: process next event for agent
    R->>T: execute required actions
    T-->>R: outputs + state updates
    R->>C: outbound reply / webhook / follow-up
    R->>Q: continue or sleep

This gives you continuity for real workflows: queued work, retries, deferred actions, and predictable wake/sleep behavior.

Production Browser Runtime

Gobii is based on browser-use and adds production runtime behavior around it.

  • Headed browser support for realistic web workflows.
  • Persistent browser profile handling for long-running agents.
  • Proxy-aware browser and HTTP task routing for controlled egress paths.
  • Task-level API compatibility via /api/v1/tasks/browser-use/.

Identity, Channels, and Agent-to-Agent

Gobii treats agents as operational entities, not just prompt sessions. When channels are enabled, each agent can be assigned identity endpoints and contacted directly like an AI coworker.

  • Agents can own communication endpoints (email, SMS, web).
  • Managed deployments support first-party agent identities like [email protected].
  • Inbound email/SMS/web events can wake agents and route into the same runtime lifecycle.
  • Agents can directly message linked peer agents for native coordination.
flowchart LR
    U[Team member] --> E[Agent email or SMS endpoint]
    E --> A[Assigned always-on Gobii agent]
    A <--> P[Peer Gobii agent]
    A --> R[Reply back to human channel]

Security Posture

Gobii's architecture is built for production guardrails.

  • Encrypted secrets integrated into agent tooling.
  • Proxy-governed outbound access with health-aware selection and dedicated proxy inventory support.
  • Sandboxed compute support for isolated tool execution.
  • Kubernetes backend support with gVisor runtime-class integration in sandbox compute paths.

For sandbox compute design references:

Launch in 5 Minutes

  1. Prerequisites: Docker Desktop (or compatible engine) with at least 12 GB RAM allocated.
  2. Clone the repo.
git clone https://github.com/gobii-ai/gobii-platform.git
cd gobii-platform
  1. Start Gobii.
docker compose up --build
  1. Open Gobii at http://localhost:8000 and complete setup.
  • Create your admin account.
  • Choose model providers (OpenAI, OpenRouter, Anthropic, Fireworks, or custom endpoint).
  • Add API keys and preferred model configuration.
  1. Create your first always-on agent.

Optional runtime profiles:

  • docker compose --profile beat up for scheduled trigger processing.
  • docker compose --profile email up for IMAP idlers and inbound email workflows.
  • docker compose --profile obs up for Flower + OTEL collector observability services.

API Quick Start

curl --no-buffer \
  -H "X-Api-Key: $GOBII_API_KEY" \
  -H "Content-Type: application/json" \
  -X POST http://localhost:8000/api/v1/tasks/browser-use/ \
  -d '{
        "prompt": "Visit https://news.ycombinator.com and return the top headline",
        "wait": 60,
        "output_schema": {
          "type": "object",
          "properties": {
            "headline": {"type": "string"}
          },
          "required": ["headline"],
          "additionalProperties": false
        }
      }'

Deployment Paths

Self-host (this repo) Gobii Cloud (managed)
MIT-licensed core on your own infrastructure Managed Gobii deployment and operations
Full runtime/networking/integration control Governed releases and managed scaling
Best for source-level customization Best for faster production rollout

Operational Profiles

Gobii keeps the default boot path simple, then lets you add worker roles as needed.

Profile Command What it adds
Core docker compose up --build App server + worker + Redis + Postgres + migrations/bootstrap
Scheduler docker compose --profile beat up Celery beat + schedule sync for cron/event timing
Email listeners docker compose --profile email up IMAP idlers for inbound email automation
Observability docker compose --profile obs up Flower + OTEL collector services

Production Use Cases

  • Revenue ops agents: monitor inboxes and web systems continuously, update records, and send structured summaries.
  • Recruiting ops agents: source candidates, enrich profiles, and coordinate outbound messaging from persistent workflows.
  • Support and success agents: triage inbound channels, execute browser-backed actions, and escalate with full state continuity.
  • Back-office automation: run long-lived, trigger-driven workflows that need durable memory and secure credentials handling.

FAQ

Is Gobii just a UI around browser-use?

No. Gobii is based on browser-use, but adds persistent agent runtime behavior: schedule/event lifecycle, comms channels, webhooks, memory, orchestration, and operational controls.

Is Gobii built for personal assistant usage?

Gobii can power individual workflows, but the architecture is tuned for team and business operations where agents stay active and integrate into production systems.

Does Gobii support headed browsers?

Yes. Gobii supports headed browser workflows and persistent profile handling for realistic web task execution.

Can each agent be contacted directly like a coworker?

Yes. With channels configured, each agent can be assigned its own endpoint identity (email and/or SMS), so your team can interact with it directly and asynchronously.

What does “always-on” mean here?

Agents can wake from schedules and external events (email/SMS/webhooks/API), process durable queued work, and continue across turns instead of resetting every interaction.

What is the security model?

Gobii integrates encrypted-at-rest secrets, proxy-aware outbound controls, and sandbox compute support with Kubernetes/gVisor backend options for stronger isolation.

Developer Workflow

Use DEVELOPMENT.md for the complete local setup and iteration flow.

Typical loop:

# backing services
docker compose -f docker-compose.dev.yaml up

# app server
uv run uvicorn config.asgi:application --reload --host 0.0.0.0 --port 8000

# workers (macOS-safe config)
uv run celery -A config worker -l info --pool=threads --concurrency=4

Docs and Deep Dives

Contributing

  • Open issues and PRs are welcome.
  • Follow existing project style and test conventions.
  • Join the community on Discord.

License and Trademarks

  • Source code is licensed under MIT.
  • Gobii name and logo are trademarks of Gobii, Inc. See NOTICE.
  • Proprietary mode and non-MIT components require a commercial agreement with Gobii, Inc.

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