
概览
主要功能
- 自主AI代理创建
- 基于目标的任务执行
- 基于Web的界面,无需安装
- 可定制的代理角色和指令
- 重复任务的工作流程自动化
- 可重复使用的代理模板
价格
- 模型
- Free
- 分类
- 緶制器
- 评分
- 4.3 / 5 (4)
使用场景
自动化重复研究任务
部署自主代理,收集信息,整理发现结果,并在多个来源中提供摘要研究,无需人工监督。
大规模起草内容
配置具有特定角色和指令的代理来处理多步骤内容起草工作流程,将团队从日常写作任务中解放出来。
跨项目重用代理
一次性构建定制代理模板,并在不同项目或团队工作流程中重用,以标准化重复的数字过程。
卸载例行流程自动化
为代理分配目标,通过浏览器自主执行多步骤业务流程,减少专业人士和团队的手动工作量。
优点 & 缺点
优点
- 浏览器中无需代码的代理设置
- 自主处理多步骤任务
- 适用于不同用例的可定制代理
- 对个人和团队都很有用
缺点
- 输出质量取决于任务复杂性
- 可能需要迭代来优化代理提示
- 代理决策的透明度有限
对决战绩
在万神殿中参与了 1 对决。
Last battle
评测
4 个评分的平均值。
登录以留下评测。
Use it every day
Honestly didn't expect to like it this much. Goal-based task execution is exactly what I needed, and handles multi-step tasks autonomously. I do wish limited transparency into agent decisions, but I reach for it almost every day now and it just clicks.
Skeptical, then convinced
I went in skeptical — most tools in this space overpromise. It actually delivers on goal-based task execution, and handles multi-step tasks autonomously caught me off guard. Output quality depends on task complexity is why this isn't a perfect score, still, I'd recommend giving it a real trial.
Compared a few options
Evaluated this against two competitors. Where it wins: autonomous AI agent creation and useful for both individuals and teams. Where it lags: output quality depends on task complexity. On balance the feature set — especially workflow automation for repetitive tasks — justifies the 4 stars for our use case.
Years in this space
I've evaluated a lot of these over the years. What stands out here is autonomous AI agent creation — handled better than most — and handles multi-step tasks autonomously. Output quality depends on task complexity is my one real gripe. Worth the time if this is your use case.
问答
Does AI Agent train models on my data? Is my data safe?
No — AI Agent does not use your data to train AI models. Your workflows, documents, and any data your agents process remain private to your account. All data is encrypted in transit and at rest. Access controls mean only members of your organisation can see your agents and their outputs. We do not share your data with third parties or use it to improve AI models. For teams with stricter requirements, enterprise plans include additional controls such as audit logs and SSO.
Asked by Dumisani Ndlovu · Jul 2, 2026
How do AI agents connect to the tools I already use?
AI Agent connects to hundreds of tools through native integrations and the Model Context Protocol (MCP), an open standard for giving AI agents access to external systems. You authenticate once per tool (OAuth or API key), and your agents can then read and write to those systems as part of any workflow. Common integrations include Gmail, Google Calendar, Slack, Notion, HubSpot, GitHub, Stripe, PostHog, and many more. New integrations are added regularly.
Asked by Zeynep Aydin · Jun 8, 2026
What can AI agents actually do?
AI agents on AI Agent can handle a wide range of tasks across every team function: - **Marketing:** Research competitors, draft campaign briefs, monitor brand mentions, generate SEO content - **Sales:** Qualify leads, enrich CRM records, draft personalised outreach, follow up on open deals - **Operations:** Triage support tickets, summarise meetings, route tasks, generate status reports - **Product:** Analyse user feedback, track feature requests, synthesise research from multiple sources - **Finance:** Pull data from dashboards, flag anomalies, draft expense summaries If it involves gathering information, making a decision, and taking an action — an AI agent can do it.
Asked by Tobias Hartmann · Jun 3, 2026
How are AI agents different from chatbots?
A chatbot is reactive — it waits for a user to send a message and responds within that conversation. It has no persistent memory between sessions and cannot take actions outside the chat window. An AI agent is proactive and goal-directed. It can run on a schedule, be triggered by external events, use multiple tools in sequence, maintain memory across sessions, and work toward a multi-step objective without waiting for a human to prompt each step. In short: chatbots answer questions; AI agents complete tasks.
Asked by Miriam Cohen · May 25, 2026
What are the common applications of AI agents in business?
AI agents are being used across every business function: - **Marketing:** Competitive analysis, content drafts, SEO monitoring, lead enrichment - **Sales:** CRM updates, personalised outreach sequences, deal summaries - **Customer support:** Ticket triage, draft replies, escalation routing - **HR:** Onboarding task coordination, policy Q&A, benefits summaries - **Finance:** Reporting, anomaly detection, invoice processing - **Product:** User research synthesis, feature request tracking, changelog drafts AI Agent lets you build agents for any of these use cases using a visual builder, no engineering required.
Asked by Jamal Carter · May 24, 2026
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