An autonomous AI agent platform: you give an agent a goal in plain English and it plans, uses real tools, and delivers the finished work.

Is there a free plan?

Yes. Actus has a free plan to get started, with paid plans that add higher limits and advanced features like scheduled automations and team workspaces.

Can agents run automatically on a schedule?

Yes — agents can run hourly, daily, or on a custom cadence, so routine work happens automatically without you starting it each time.

How is Actus different from a chatbot?

A chatbot replies with text. An Actus agent takes action: it uses real tools to research, write, build, and send, then returns a finished deliverable instead of just advice.

Do I need to know how to code?

No. You describe your goal in plain English and the agent plans and executes the steps. Agents can write and run code when a task needs it, but you never have to.

Do I stay in control of what an agent does?

Yes. Irreversible actions require your approval, every run has budget and step limits, and each step is logged so you can see exactly what happened.

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AI Agent vs Traditional Chatbot

Actus · September 30, 2026

AI agentschatbotsbusiness automationworkflow automationAI comparison

AI Agent vs Traditional Chatbot

A chatbot answers questions. An AI agent completes work. That is the fundamental difference. Chatbots are conversational interfaces trained to provide information or route requests. AI agents are autonomous systems that research, decide, execute multi-step workflows, and produce outcomes without continuous human prompting.

What Chatbots Do

Traditional chatbots operate within narrow parameters:

Answer frequently asked questions from a knowledge base.
Route customer inquiries to the right department.
Capture form data through conversational prompts.
Provide scripted responses based on keywords or intent detection.

Chatbots excel at reducing support volume and improving response time for common questions. They do not perform research, make complex decisions, or execute workflows across multiple systems.

What AI Agents Do

AI agents go beyond conversation. They:

Research leads by visiting websites, scraping data, and cross-referencing sources.
Make decisions based on business context (qualified or not, urgent or routine, in-scope or out-of-scope).
Execute multi-step workflows (research → draft → send → log → schedule follow-up).
Update records across CRM, spreadsheets, task management, and communication tools.
Adapt to exceptions and incomplete data instead of failing.

An agent can complete an entire lead qualification workflow autonomously. A chatbot can only ask the qualification questions and pass the answers to a human.

When to Use Each

Use a chatbot when:

The goal is to answer common questions at scale.
The workflow is simple and linear (capture contact info, route to sales).
You need a front-end for customers or website visitors.
The outcome is information delivery, not task execution.

Use an AI agent when:

The workflow has multiple steps and requires coordination across tools.
Decisions must be made based on context, not just keywords.
The goal is to complete work, not just gather information.
You need autonomous execution with human review at key checkpoints.

Example: Lead Qualification

Chatbot approach: The chatbot asks the visitor: "What service are you interested in? What is your location? What is your email?" It logs the responses and notifies a sales rep to follow up.

AI agent approach: The agent reads the inquiry (whether it came from a form, DM, email, or chatbot), researches the company if it is a business inquiry, checks whether the location is in the service area, scores the lead based on fit and urgency, drafts a personalized reply, and either sends a booking link or routes to a human for complex cases.

The chatbot captured data. The agent completed the qualification workflow.

Chatbots Are Reactive; Agents Are Proactive

Chatbots wait for a user to initiate a conversation. Agents can trigger workflows based on events:

A lead has not replied in 3 days → send a follow-up.
An estimate was sent 5 days ago with no response → send a reminder.
A new lead appeared in a scraping workflow → research, enrich, and draft outreach.

This makes agents useful for recurring, scheduled work that happens without human prompting.

Integration Depth

Chatbots typically integrate with one or two systems: a knowledge base and a CRM. Agents integrate with the full stack: CRM, email, calendar, task management, research tools, data sources, communication channels, and document generation.

A chatbot can create a CRM record. An agent can create the record, enrich it with external data, assign it to the right team member, schedule a follow-up task, and draft an email for review.

Cost and Complexity

Chatbots are cheaper and faster to deploy. Many platforms offer no-code chatbot builders with templates for common use cases. Setup takes hours or days.

AI agents require more upfront work: defining workflows, mapping decision logic, connecting tools, and testing with real data. Setup takes days or weeks. The payoff is higher because agents replace entire workflows, not just the first touchpoint.

Do You Need Both?

Yes, in many cases. A chatbot can be the front-end interface that captures inquiries, and an AI agent can be the back-end system that processes them. The chatbot provides a friendly user experience. The agent does the operational work.

For example:

A website visitor uses a chatbot to request a quote.
The chatbot captures their details and passes them to an agent.
The agent researches the company, checks service area fit, drafts a personalized response, and either sends it or routes to a human if the inquiry is complex.

The chatbot improved the user experience. The agent improved the operational efficiency.

Common Misconceptions

"Chatbots can do everything agents do if you configure them well." No. Chatbots are designed for conversation, not execution. They cannot autonomously research, draft documents, update multiple systems, or run recurring workflows.

"AI agents will replace all chatbots." No. Chatbots are still the best tool for customer-facing FAQ interfaces and simple data capture. Agents are better for back-office workflows.

"Agents are just chatbots with more integrations." No. The difference is architectural. Chatbots are reactive and conversational. Agents are proactive and execution-focused.

Real-World Comparison

Scenario: New inquiry from a website form

Chatbot:

Form submission triggers a notification.
Chatbot sends an auto-reply: "Thanks for your inquiry. Someone will reach out within 24 hours."
A human manually reviews the inquiry, researches the company, drafts a reply, and sends it.

AI Agent:

Form submission triggers the agent.
Agent extracts details, researches the company website, checks service area, scores the lead.
Agent drafts a personalized reply referencing the company's specific needs.
Agent sends the reply (or routes to human if complex) and logs everything in the CRM.

The chatbot sent a generic acknowledgment. The agent completed the qualification and response workflow.

When to Upgrade from Chatbot to Agent

You should consider an AI agent when:

Your chatbot collects data but someone still has to manually process every inquiry.
You need workflows that span multiple tools and steps.
Your team spends hours each week on repetitive coordination (research, drafting, logging, scheduling).
You want proactive workflows that run on a schedule, not just reactive responses.

Why Actus Agent

Actus Agent is built for autonomous workflow execution. It connects research, decision-making, communication, and record-keeping into complete processes. While chatbots stop at conversation, Actus completes the work.

Learn more at actusagent.cc