What AI models does the agent use?

The agent has access to Claude, DeepSeek, Gemini, and other top models. It automatically routes to the best model for each task — you never have to think about API keys or token limits.

Yes. Each agent runs in an isolated environment. We don't train on your data, and you can export or delete everything at any time. The underlying engine (GoGogot) is open-source, so you can audit exactly how it works.

What can the agent actually do?

Browse the web, process files (CSV, PDF, images), run scheduled tasks, remember context across sessions, and communicate via Telegram or Slack. Think of it as a capable junior employee, not a chatbot.

How does memory work?

The agent maintains persistent memory across sessions. It remembers your preferences, past conversations, and task context. You can also explicitly tell it to remember or forget things.

Can I self-host the agent?

Absolutely. GoGogot is 100% open-source. Run it on your own hardware for free. cowork.ink is the managed version — we handle servers, model costs, updates, and uptime so you don't have to.

Is there a free trial?

We offer a 7-day money-back guarantee. Spin up an agent, give it real tasks, and if it doesn't save you time, we'll refund you — no questions asked.

What is an agent swarm in AI?

An agent swarm is a multi-agent system where several specialized AI agents collaborate toward a shared objective. Each agent handles a narrow task — like research, validation, or summarization — and the group produces results no single agent could achieve alone. Learn more in our [guide to AI agent orchestration](/blog/ai-agent-orchestration/).

When should you use an agent swarm instead of a single agent?

Use an agent swarm when the task is parallelizable, requires multiple areas of expertise, or is too complex for one agent to handle reliably. Google research found that swarms improve performance by up to 80% on parallelizable tasks, but degrade it on strictly sequential ones.

What are the main agent swarm orchestration patterns?

The five common patterns are orchestrator-worker (centralized delegation), hierarchical (tree-structured), pipeline (sequential stages), mesh (peer-to-peer), and swarm (decentralized emergent coordination). Most production systems use hybrids.

Are agent swarms better than single agents?

Not always. Swarms excel at parallel, multi-faceted tasks but add overhead that hurts strictly sequential reasoning — degrading performance by 39–70% in some benchmarks. The right choice depends on your task structure.

Agent Swarms Explained: When Many Agents Beat One

What is an agent swarm? Learn how multiple AI agents collaborate, KEY orchestration patterns, and when swarms beat single agents. Explore now.

Frequently Asked Questions

What is an agent swarm in AI?: An agent swarm is a multi-agent system where several specialized AI agents collaborate toward a shared objective. Each agent handles a narrow task — like research, validation, or summarization — and the group produces results no single agent could achieve alone. Learn more in our [guide to AI agent orchestration](/blog/ai-agent-orchestration/).
When should you use an agent swarm instead of a single agent?: Use an agent swarm when the task is parallelizable, requires multiple areas of expertise, or is too complex for one agent to handle reliably. Google research found that swarms improve performance by up to 80% on parallelizable tasks, but degrade it on strictly sequential ones.
What are the main agent swarm orchestration patterns?: The five common patterns are orchestrator-worker (centralized delegation), hierarchical (tree-structured), pipeline (sequential stages), mesh (peer-to-peer), and swarm (decentralized emergent coordination). Most production systems use hybrids.
Are agent swarms better than single agents?: Not always. Swarms excel at parallel, multi-faceted tasks but add overhead that hurts strictly sequential reasoning — degrading performance by 39–70% in some benchmarks. The right choice depends on your task structure.