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 in HR?

AI agents in HR are autonomous software systems that can perform multi-step tasks like screening resumes, scheduling interviews, answering employee questions, and orchestrating onboarding workflows — without constant human oversight. Unlike simple chatbots, they reason, plan, and take action across connected HR systems. Learn more in our [guide to AI agents](/blog/ai-agents-explained/).

Will AI agents replace HR professionals?

No. AI agents handle repetitive, high-volume tasks like screening, scheduling, and policy lookups — freeing HR professionals to focus on strategy, culture, and complex employee relations. IBM's AskHR handles 10.1 million interactions per year, but humans still make final hiring and termination decisions.

How much can AI agents save in HR?

Organizations report 40–50% reduction in manual HR effort. Unilever saved over $1 million per year in recruiting costs and cut time-to-hire by 75%. On average, recruiters save 15–20 hours per week using AI agents for screening and scheduling.

What are the risks of using AI in HR?

The main risks are algorithmic bias in hiring decisions, data privacy concerns with employee information, and over-reliance on automation for sensitive decisions. Teams should implement fairness audits, maintain human oversight for final decisions, and ensure compliance with employment regulations.

AI Agents for HR: Recruiting, Onboarding & Beyond

Discover how AI agents for HR automate recruiting, onboarding, and employee experience. TOP tools, real ROI stats, and implementation tips. Learn more.

Frequently Asked Questions

What are AI agents in HR?: AI agents in HR are autonomous software systems that can perform multi-step tasks like screening resumes, scheduling interviews, answering employee questions, and orchestrating onboarding workflows — without constant human oversight. Unlike simple chatbots, they reason, plan, and take action across connected HR systems. Learn more in our [guide to AI agents](/blog/ai-agents-explained/).
Will AI agents replace HR professionals?: No. AI agents handle repetitive, high-volume tasks like screening, scheduling, and policy lookups — freeing HR professionals to focus on strategy, culture, and complex employee relations. IBM's AskHR handles 10.1 million interactions per year, but humans still make final hiring and termination decisions.
How much can AI agents save in HR?: Organizations report 40–50% reduction in manual HR effort. Unilever saved over $1 million per year in recruiting costs and cut time-to-hire by 75%. On average, recruiters save 15–20 hours per week using AI agents for screening and scheduling.
What are the risks of using AI in HR?: The main risks are algorithmic bias in hiring decisions, data privacy concerns with employee information, and over-reliance on automation for sensitive decisions. Teams should implement fairness audits, maintain human oversight for final decisions, and ensure compliance with employment regulations.