10 Best AI Agents for Small Business (2025): Tested & Reviewed

AI agents can save small teams hours each week by handling follow-ups, updating CRMs, and routing internal tasks. But with so many platforms out there, picking the right one isn’t easy. 

If you want fast setup and customizable AI workflows, Lindy stands out. It lets you launch configurable AI agents without code. Other strong picks include Relevance AI for internal data tasks and Make for visual workflows.

In this article, we’ll cover:

• The 10 best AI agents for small businesses
• What AI agents do differently from bots
• How small businesses are using agents today
• Which tools are the easiest to use
• How to choose the right one for your stack and team

First, we take a quick look at the top 10 tools we shortlisted.

The 10 best AI agents for small business: TL;DR

These AI agents are designed to automate real work across sales, ops, or support. Whether you're looking for a flexible AI agent app or something more technical, there's a mix here for different needs and skill levels. 

Here’s a quick rundown of the top AI agent tools for small businesses:

1. Lindy – Best for all-in-one automation across sales, ops, and support
2. Relevance AI – Best for building modular agents powered by your internal data
3. CrewAI – Best for multi-agent collaboration and task orchestration
4. AutoGen – Best for custom research and content generation using LLMs
5. Make – Best for visual no-code workflows that connect multiple apps
6. Postman – Best for API-first automation with LLM integrations
7. Botpress – Best for building conversational AI agents and support workflows
8. Zencoder – Best for developer-friendly agent chaining and backend logic
9. LangChain + LangGraph – Best for building complex, custom AI applications
10. Zapier – Best for prompt-driven task automation with broad integrations

Let’s now explore each of these tools in detail.

1. Lindy – Best all-in-one AI agent for ops, sales & support

Lindy is a no-code AI automation platform that lets you build AI agents to help automate your daily tasks. If you're looking for a single AI agent tool to take repetitive tasks off your plate — from triaging emails to updating your CRM — Lindy is a strong place to start. 

Lindy agents can understand a simple task like updating tools like Slack or Salesforce. Or it can handle more advanced, multi-step workflows like qualifying a lead, scheduling a meeting, and logging details to your CRM. The best thing is that you don’t need a technical background to get started. 

It’s great for small teams managing inbound leads, client requests, and backend workflows.

Features

• No-code agent builder
• 7,000+ integrations, native integrations with tools like Gmail, Slack, Notion, and Stripe
• Templates for meeting scheduling, lead routing, CRM updates, email follow-ups, and more
• Multi-agent collaboration, for example, triage → update CRM → email handoff
• Works across email, voice, Slack, docs, and more
• SOC 2 and HIPAA compliance
• Remembers past interactions and lets you adjust agent behavior to match your tasks

Pros

• Quick to launch with no-code setup
• Designed specifically for SMBs 
• Prebuilt, ready-to-use templates save time from day one
• Works across mediums –– email, calls, web forms

Cons

• Less customizable for devs compared to open-source frameworks
• Needs some setup time to configure complex workflows

Pricing

• Free plan: 400 credits/month
• Pro: $49.99/month for 5,000 credits
• Business: $299.99/month for 30,000 credits

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2. Relevance AI – Best for modular agents powered by internal data

Relevance AI is a low-code AI agent app that lets teams build modular agents that act on internal business data. It's built for users with some technical background who want agents to interpret inputs, understand context, and carry out tasks.

If you're automating internal analytics, multi-step workflows, or support triage that relies on past data, Relevance gives you more control than typical no-code tools. It works especially well in ops and marketing teams that need custom logic but don’t want to write full code.

Features

• Workflow agent builder with role memory
• Knowledge storage using vector search
• API + CRM integrations
• Prebuilt templates for support triage, lead scoring, reporting

Pros

• Strong memory and context retention
• Works well with semi-structured internal data
• More flexible logic than standard drag-and-drop tools

Cons

• Designed for technical users
• Setup requires understanding APIs and internal data structures

Pricing

• Free plan available
• Pro: $19/month
• Team: $199/month
• Business: $599/month

3. CrewAI – Best for multi-agent collaboration and orchestration

CrewAI is an open-source agent tool that lets developers create multi-agent workflows where different agents take on roles, communicate, and coordinate to complete tasks. It’s built for technical teams that want deep control over how agents collaborate.

If you're building custom internal tools, experimenting with autonomous workflows, or need agents to handle specialized subtasks in sync, CrewAI is one of the more structured frameworks out there. Think of it as a skeleton for agent teamwork.

Features

• Role-based agent assignment and task orchestration
• Works with LangChain and external APIs
• Open-source and self-hostable
• Supports agent “crew” logic for delegated tasks

Pros

• High visibility into agent behavior
• Great for building custom LLM workflows
• Active open-source community

Cons

• Requires Python and infra knowledge
• No UI or onboarding, it’s code-first
• Not suited for founders without technical resources

Pricing

• Free via GitHub (open-source)
• Paid Basic tier starts at $99/month

4. AutoGen – Best for custom research and generation workflows

AutoGen is an open-source framework for building multi-agent systems that collaborate on research, content generation, or reasoning tasks using large language models. It’s designed for AI engineers, data teams, and R&D groups — not business users.

If you need agents that can talk to each other, analyze data, and iterate on outcomes (like summarizing reports, exploring research queries, or debugging code), AutoGen gives you building blocks to set that up. But it’s a backend framework, not a plug-and-play AI agent app.

Features

• Multi-agent collaboration framework
• Configurable LLM flows with memory
• Supports various model providers (OpenAI, Azure, etc.)
• Local or cloud deployment

Pros

• Completely free and open-source
• Flexible and extendable
• Great for experimentation and LLM-heavy workflows

Cons

• No UI — setup is entirely code-based
• Requires experience with Python and infra
• No integrations or templates out of the box

Pricing

• Free, open-source
• Users pay only for LLM/API usage

5. Make – Best for visual no-code workflows across apps

Make is a visual automation platform that lets you create workflows by connecting different apps through a drag-and-drop interface. While it wasn’t built as an AI-first product, it now supports agent tools that use reasoning and decision logic.

It’s ideal for founders or ops leads who want to automate things like lead handoffs, invoice approvals, or multi-step onboarding — without touching code. If you want more flexibility, this is a solid next step.

Features

• Visual workflow builder with branching logic
• 2,000+ app integrations
• AI modules for reasoning and data manipulation
• Schedule or trigger-based automations

Pros

• Friendly UI for building complex automations
• Great flexibility with app connections and data flows
• Easy to test, tweak, and iterate

Cons

• AI capabilities aren’t deeply integrated
• Can get expensive at a higher volume
• Not built around autonomous agents

Pricing

• Free plan available
• Paid plans start from $10.59/month, billed monthly

6. Postman – Best for API-first automation with LLMs

Postman is an agent tool built for teams already working with APIs. It combines Postman’s robust API infrastructure with LLM-powered agents, allowing developers to build workflows that trigger actions, query APIs, or reason over responses.

It’s best for technical teams that want to add automation or AI reasoning to their existing API workflows. If your ops depend on backend systems and structured data, Postman gives you a programmable middle layer to build on.

Features

• Drag-and-drop builder –– Postman Flows
• Multi-LLM support –– OpenAI, Anthropic, and more
• Native API query + transformation steps
• Version control and environment support

Pros

• Ideal for complex, data-driven workflows
• Built for reliability and observability
• Leverages existing Postman knowledge

Cons

• Not designed for non-technical users
• Limited in use cases outside developer-driven ops
• Lacks templates or out-of-the-box workflows

Pricing

• Free tier available
• Paid plans are usage-based, start from $19/month, billed monthly

7. Botpress – Best for building conversational AI agents

Botpress is an open-source AI agent app built for creating conversational agents. It's focused entirely on natural language understanding, making it ideal for businesses that want agents to talk to users over chat or messaging platforms.

It’s best suited for technical teams building custom chat interfaces, voice agents, or embedded assistants. Also, it suits support flows, internal HR bots, or Slack-based helpdesks — not end-to-end sales or ops automation.

Features

• NLP engine with intent recognition and slot filling
• Visual conversation flow builder
• Integrates with Slack, MS Teams, Twilio, and more
• Open-source and customizable

Pros

• Strong conversational AI capabilities
• Flexible for devs to customize behaviors
• Good for building support-facing agents

Cons

• Limited to chat-first use cases
• Requires some technical setup
• Doesn’t support multi-app workflows out of the box

Pricing

• Free tier available
• Paid plans start from $89/month, billed monthly

8. Zencoder – Best for chaining developer-first agents

Zencoder is a developer-focused agent tool built for chaining AI agents together in structured workflows. It’s CLI-first (Command Line Interface) and API-heavy. 

It’s designed for technical users who want to automate backend processes like data labeling, content generation, or internal analysis through programmable agents. Zencoder suits teams building agent pipelines with complex logic, sequencing, or cross-agent coordination.

Features

• Agent chaining with task handoff
• SDK + CLI support
• Webhook and event-based execution
• Compatible with custom LLM calls

Pros

• Flexibility for structured agent logic
• Can integrate deeply into internal systems

Cons

• No UI or templates — devs only
• Still early-stage with limited docs
• Not viable for small teams without engineering bandwidth

Pricing

• Starts free
• Paid plans begin from $19/month, billed monthly 

9. LangChain + LangGraph – Best for building custom AI applications

LangChain and LangGraph are open-source frameworks that let developers build advanced AI agent apps with memory, tool use, and autonomous behavior. 

LangChain handles the logic and tools and LangGraph adds structured workflows, like loops and state transitions between agents.

These are best suited for startups, AI labs, or R&D teams building custom apps, not workflow automation for SMBs. If you're shipping an LLM-powered product and need control over agent behavior, tool use, and memory, this is where most people start.

Features

• Tool chaining and memory management
• Multi-agent graphs with async transitions
• Support for OpenAI, Anthropic, Cohere, etc.
• Integrates with APIs, DBs, and custom tools

Pros

• Flexibility for app-level use cases
• Huge open-source ecosystem
• Ideal for full product builds, not just workflows

Cons

• No UI or prebuilt flows
• High learning curve — built for engineers
• Requires infra and LLM management

Pricing

• Free, self-hosted for hobbyists
• Infra and LLM usage billed separately
• Paid plans start from $39/developer/month

10. Zapier – Best for simple, repetitive task automation

Zapier is a lightweight AI agent app for task-based automation, not multi-agent logic. 

Zapier AI adds a natural language layer to Zapier’s automation platform. Instead of manually configuring Zaps, you can describe what you want to automate, and the system builds the workflow for you. It’s a 

It’s best for small teams that already use Zapier and want to move faster — without needing more logic or infrastructure.

Features

• AI Copilot for workflow suggestions
• Prompt-to-Zap builder
• Access to 7,000+ apps and triggers
• Runs in the existing Zapier interface

Pros

• Familiar UX for existing Zapier users
• Low barrier to entry
• Great for simple automations like lead routing, reminders, and more

Cons

• Not built for agent coordination or memory
• No native long-term task management
• Limited reasoning capabilities compared to agent frameworks

Pricing

• Free: 100 tasks/month
• Paid plans from $29.99/month, billed monthly

You’ve seen what each tool does. But if you’re skimming or trying to narrow your shortlist, here’s how they stack up at a glance.

Top AI agent tools: a quick comparison

This table highlights what each platform is best for, who it’s built for, and whether it fits into a no-code workflow or something more technical. Let’s see how they compare:

Now that we’ve looked at the tools, let’s understand how we reviewed them. 

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How I tested these AI agent tools

The goal here was to answer one question –– can these AI agents replace everyday tedious tasks without adding new complexity? Here’s what I looked for:

• Ease of setup: Can someone on the team (who isn’t a developer) get value out of it in under a day?
• Breadth of tasks: Does it go beyond just answering messages or moving data? Can it run parts of a workflow?
• Integrations: Does it connect to tools small businesses already use — like Gmail, Notion, Slack, HubSpot, or Stripe?
• Price-to-value: Is the free or entry-level plan usable? And does it scale without spiking costs?
• Reliability: Does it hold context? Can agents run with minimal human intervention and not need babysitting?

This gave a clear sense of which agent tools are helpful right away — and which ones are better left to technical teams or experimental use cases.

A lot of tools blur the line between chatbots, automation platforms, and AI agents. But the differences matter. Let’s see why.

AI agents vs. chatbots: how are they different?

AI agents are goal-oriented. They respond and take action. A chatbot might answer a question, but an agent will recognize a lead, update the CRM, and schedule a follow-up.

Here’s a breakdown to keep things simple:

If you’re wondering what this looks like in a business context, here’s where AI agents pull real weight. We uncover that next.

What can small businesses automate with AI agents?

AI agents are digital workers who can handle routine tasks across teams without needing constant supervision. Here’s what small teams are already automating today:

• Lead intake and enrichment: Agents can read inbound form fills or emails, enrich leads using tools like Clearbit or LinkedIn, and qualify or route them based on logic.
• CRM updates and outreach: Instead of relying on manual updates, agents can auto-log activity, tag accounts, and even send follow-ups when leads go cold.
• Meeting summaries and handoffs: Whether it's parsing call transcripts or Slack messages, agents can summarize conversations and assign next steps automatically.
• Sales forecasting and pipeline hygiene: Agents can monitor deals, nudge reps about inactivity, and flag accounts that need attention.
• Customer support triage: Agents classify inbound emails or support tickets, handle known issues, and escalate edge cases to your team.
• Slack → CRM handoffs: When someone drops a lead in a team channel, an agent can log it, update the CRM, and schedule the next step — no copy-pasting needed.

If you’re already exploring how to use AI in business, this is where things start to move from ideas to workflows.

Some AI tools are either too technical, too narrow or just don’t work across the tools you use. But Lindy is different. Here’s how.

Why Lindy is built for small business agents

Lindy is a no-code AI automation tool that acts more like an ops teammate than a workflow builder. It’s built to automate the boring stuff — routing leads, sending follow-ups, updating your CRM — across your existing stack, without needing devs.

Here’s where it stands out for lean teams:

• Works across your stack: Agents operate via email, Slack, phone, calendar, and docs. You can create agents for different steps of a workflow — like one to triage customer requests and another to log notes in Notion or Salesforce — by defining clear handoffs using no-code triggers and logic.
• Prebuilt templates that work: Use cases like lead follow-up, employee onboarding, and internal alerts — already built. You do not need to configure from scratch.
• No-code setup: You can build and deploy agents as an ops lead or founder. Just use the visual drag-and-drop workflow builder or modify the ready-to-use templates.
• Async agent collaboration: One agent qualifies a lead. Another follows up. Another handles scheduling. Agents pass context and execute together.
• Flexible pricing: Start free with 400 credits/month, and scale up as you grow.

If you’re looking for more than just a trigger-action builder, and want something that feels closer to a real assistant, Lindy is worth considering.

Frequently asked questions

What’s the best AI agent platform for small businesses?

If you want something you can use without writing code, tools like Lindy, Zapier AI, or Make are solid. If you’ve got engineering resources and want to build custom workflows, CrewAI or LangChain gives you deeper control.

How is an agent different from a chatbot or workflow tool?

Chatbots respond. Agents act. A chatbot might answer a question, but an agent can route a lead, send a follow-up, and log the outcome in your CRM — all based on context. They’re more flexible than most AI chatbot tools and more autonomous than workflow builders.

Can AI agents handle real tasks like CRM updates or follow-ups?

Yes, AI agents can handle tasks like CRM updates and follow-ups. Some platforms also support voice-based agents that speak with leads directly. That’s where they’re most useful, particularly for sales and support workflows.

Are AI agents worth the cost for small businesses?

Yes, they are of great value if your team is stretched thin or doing too many repetitive tasks. A well-designed agent can reduce repetitive tasks and free up time — helping teams work more efficiently without adding extra tools or headcount.

Lindy, your no-code AI agent platform

If you’re looking for an easy-to-use AI solution that provides automations around emails, meetings, and sales, go with Lindy. 

Out of all the AI agent platform, here’s why we believe Lindy stands out and provides the most value:

• Simple no-code interface: You won’t need coding, programming, or technical skills to create your automations with Lindy — it offers a drag-and-drop visual workflow builder. 

• AI agents customized to your needs: You can make versatile AI agents that understand plain English and accelerate your productivity in many ways. For instance, create an assistant that bolsters your sales funnel by finding leads from websites and business intelligence sources like People Data Labs. Create another agent that sends out emails to each lead and schedules meetings with members of your sales team. 

• Affordability: Build your first few automations with Lindy’s free version and get up to 400 tasks. With the Pro plan, you can automate up to 5,000 tasks, which offers much more value than Lindy’s competitors.  

Try Lindy today for free.