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 AI agent for customer support?

An AI agent for customer support is an autonomous software system that can understand customer intent, access backend data (orders, accounts, knowledge bases), take actions (issue refunds, reset passwords, create tickets), and resolve issues end-to-end — without scripted decision trees. Unlike basic chatbots, AI agents reason through multi-step problems and hand off to humans only when genuinely needed. Learn more in our [overview of AI agent use cases](/blog/ai-agent-use-cases/).

How is an AI agent different from a customer support chatbot?

Traditional chatbots follow rigid scripts — they match keywords to canned responses and fail the moment a customer goes off-script. AI agents reason, plan, and act: they can look up order history, process a return, check inventory, and send a follow-up — all in one conversation. The gap is enormous in practice. See our full breakdown of [AI agents vs chatbots](/blog/ai-agents-vs-chatbots/).

Can AI agents fully replace human customer service agents?

No — and Gartner warns that companies cutting too many human agents are likely to rehire by 2027. AI agents handle the high-volume, repetitive 80% extremely well. The remaining 20% — emotional complaints, novel edge cases, regulatory escalations — still require human judgment. The winning model is AI-as-first-responder with seamless escalation to humans.

What is the ROI of AI agents in customer support?

AI cuts cost per interaction from roughly $6–8 (human) to $0.50–0.70 — a 12x reduction. Documented implementations show 41% ROI in year one, climbing to 87% by year two. Klarna's AI agent cut average resolution time from 11 minutes to 2 minutes. That said, poorly configured AI can erode CSAT scores quickly, so setup quality matters enormously.

How do I get started with AI agents for my support team?

Start with one high-volume, low-complexity use case (password resets, order status, FAQ). Define clear escalation triggers, connect your knowledge base, and measure containment rate weekly. Once that channel is stable, expand to more complex flows. [cowork.ink](https://app.cowork.ink) lets teams deploy and orchestrate support agents without writing custom integrations from scratch.

AI Agents for Customer Support: Resolve 80% of Tickets

AI agents for customer support resolve up to 80% of tickets automatically. PROVEN ROI, real use cases, and a step-by-step implementation guide. Start now.

Frequently Asked Questions

What is an AI agent for customer support?: An AI agent for customer support is an autonomous software system that can understand customer intent, access backend data (orders, accounts, knowledge bases), take actions (issue refunds, reset passwords, create tickets), and resolve issues end-to-end — without scripted decision trees. Unlike basic chatbots, AI agents reason through multi-step problems and hand off to humans only when genuinely needed. Learn more in our [overview of AI agent use cases](/blog/ai-agent-use-cases/).
How is an AI agent different from a customer support chatbot?: Traditional chatbots follow rigid scripts — they match keywords to canned responses and fail the moment a customer goes off-script. AI agents reason, plan, and act: they can look up order history, process a return, check inventory, and send a follow-up — all in one conversation. The gap is enormous in practice. See our full breakdown of [AI agents vs chatbots](/blog/ai-agents-vs-chatbots/).
Can AI agents fully replace human customer service agents?: No — and Gartner warns that companies cutting too many human agents are likely to rehire by 2027. AI agents handle the high-volume, repetitive 80% extremely well. The remaining 20% — emotional complaints, novel edge cases, regulatory escalations — still require human judgment. The winning model is AI-as-first-responder with seamless escalation to humans.
What is the ROI of AI agents in customer support?: AI cuts cost per interaction from roughly $6–8 (human) to $0.50–0.70 — a 12x reduction. Documented implementations show 41% ROI in year one, climbing to 87% by year two. Klarna's AI agent cut average resolution time from 11 minutes to 2 minutes. That said, poorly configured AI can erode CSAT scores quickly, so setup quality matters enormously.
How do I get started with AI agents for my support team?: Start with one high-volume, low-complexity use case (password resets, order status, FAQ). Define clear escalation triggers, connect your knowledge base, and measure containment rate weekly. Once that channel is stable, expand to more complex flows. [cowork.ink](https://app.cowork.ink) lets teams deploy and orchestrate support agents without writing custom integrations from scratch.