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 are AI agents for business?

Business AI agents are autonomous AI systems that execute multi-step tasks on behalf of an organization — processing documents, updating CRMs, sending emails, analyzing data, and coordinating with other agents. Unlike chatbots that respond to questions, agents pursue goals, use tools, and take actions in business systems without step-by-step human direction.

What business problems do AI agents solve?

AI agents excel at processes involving unstructured inputs (emails, documents), multi-step workflows across systems, high-volume repetitive tasks with variable inputs, and workflows requiring judgment calls that rules-based automation can't handle. Common examples: customer support triage, invoice processing, lead qualification, document review.

How long does it take to deploy AI agents for business?

Template-based deployment: 1–3 days. Custom workflow: 1–2 weeks. Enterprise self-hosted with governance setup: 1–4 weeks. The most time-consuming part is usually defining the process and testing edge cases, not the actual deployment.

How are AI agents different from RPA bots?

RPA bots follow fixed scripts and break when processes change. AI agents understand goals, handle exceptions contextually, and adapt to process variations. Agents work with unstructured data (natural language, PDFs); RPA requires structured inputs. AI agents make judgment calls; RPA executes deterministic rules.

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Frequently Asked Questions

What are AI agents for business?: Business AI agents are autonomous AI systems that execute multi-step tasks on behalf of an organization — processing documents, updating CRMs, sending emails, analyzing data, and coordinating with other agents. Unlike chatbots that respond to questions, agents pursue goals, use tools, and take actions in business systems without step-by-step human direction.
What business problems do AI agents solve?: AI agents excel at processes involving unstructured inputs (emails, documents), multi-step workflows across systems, high-volume repetitive tasks with variable inputs, and workflows requiring judgment calls that rules-based automation can't handle. Common examples: customer support triage, invoice processing, lead qualification, document review.
How long does it take to deploy AI agents for business?: Template-based deployment: 1–3 days. Custom workflow: 1–2 weeks. Enterprise self-hosted with governance setup: 1–4 weeks. The most time-consuming part is usually defining the process and testing edge cases, not the actual deployment.
How are AI agents different from RPA bots?: RPA bots follow fixed scripts and break when processes change. AI agents understand goals, handle exceptions contextually, and adapt to process variations. Agents work with unstructured data (natural language, PDFs); RPA requires structured inputs. AI agents make judgment calls; RPA executes deterministic rules.