
If you're excited about building AI agents to automate complex tasks and enhance productivity, you're in the right place. AI agent builder platforms let you create intelligent agents—powered by AI models like GPT—that can handle everything from customer support and data analysis to content creation and workflow automation. These tools range from no-code platforms that anyone can use, to advanced frameworks for developers. In this post, we'll explore 11 of the top AI agent builder platforms, discussing what each does, their use cases, pros 🤩 and cons 🤔, and what real users are saying on G2. Whether you're a beginner or an enterprise tech lead, you'll find an option that fits your needs.
TL;DR 👀
- For the easiest-to-use AI agent builder (great for beginners): choose Relay.app – it offers a super intuitive interface and lots of pre-built AI capabilities ✅.
- For powerful no-code AI workflows: consider Gumloop if you need advanced, complex automations with AI integration.
- If you want an AI assistant for daily tasks: Lindy.ai is ideal for automating things like email, scheduling, and routine workflows.
- For a versatile AI agent platform with vector search: Relevance.ai provides custom AI agents with strong data analytics features.
- Need to integrate AI into thousands of apps? Zapier brings AI agents into a massive ecosystem of integrations, though its AI features are more basic.
- Prefer open-source or self-hosted solutions? n8n (workflow automation with AI nodes) and Flowise (LLM flow builder) give you full control and customization.
- For orchestrating multiple AI agents working together: CrewAI enables multi-agent “crews” for complex, collaborative tasks.
- Enterprise-scale AI platforms: Stack AI (built for enterprise deployments with analytics) or Google Vertex AI (Google Cloud’s ML platform) offer robust tools, but come with complexity.
- Community-driven AI agents: Agent.ai is a new platform featuring a network of pre-built AI agents and a low-code builder – great for discovering ready solutions.
Now, let's dive into each platform in detail:
The 11 Best AI Agent Builder Platforms in 2025
1. Relay.app
⭐ G2: 5.0 (60+ reviews)
Best for: Easy-to-use AI agent building with extensive pre-built capabilities.
Relay.app is a modern platform for building AI-powered workflows and agents. It’s designed to be incredibly easy to use, enabling non-technical users to create AI automations in minutes. With Relay, you can quickly create actions to automate routine tasks and integrate AI for things like content generation or data extraction. Relay.app also places a strong emphasis on human-in-the-loop features that keep users in control and ensures that AI agents work predictably.

Pros ✅
- Delightfully intuitive interface that makes AI agent building accessible to non-technical users.
- Extensive library of pre-built AI actions (data extraction, content generation, etc.) and templates for common use cases.
- Human-in-the-loop features for reviewing or approving actions, so you maintain control over what the AI does.
- Built-in AI credits and model integration – use GPT-4, Claude, etc., without manual API keys.
- Visual workflow builder with smart branches and conditions, allowing sophisticated agent behaviors without coding.
Cons ❌
- Integration library still growing – as a newer platform, it may not yet have every app integration that incumbents like Zapier offer
Pricing 💰
- Free Tier: Yes – includes 200 automation steps and 500 AI credits per month.
- Professional: $9/month (generous for single users or small teams).
- Team: $59/month (higher capacity and collaboration).
- Enterprise: Custom pricing for large organizations.
Takeaway: If Relay.app supports the integrations you need, it should be your first choice for building AI agents. Users praise its exceptionally easy UI and smooth experience, which is why Relay is often highlighted as the easiest-to-use AI agent builder for beginners
2. Gumloop
⭐ G2: Rising platform (limited reviews)
Best for: Complex AI agent creation with advanced workflow capabilities.

Gumloop is a no-code platform for automating repetitive and complex workflows end-to-end with AI. Think of it as a power-user automation tool: you drag, drop, and connect modular components (called “nodes”) on a canvas to design sophisticated AI-driven processes. Gumloop comes with ready-made components for tasks like data extraction, text analysis, scoring, and more, which you can chain together into multi-step workflows. It’s great for technical users or teams that want to build very custom AI workflows without coding everything from scratch – for example, a multi-step marketing campaign handler, or a complex data pipeline with AI judgments at certain steps.
Pros ✅
- Advanced AI agent customization: You can define complex logic and behaviors using a visual node-based interface, almost like building a program flowchart.
- Extensive pre-built nodes for AI tasks (e.g. language understanding, data processing), which speeds up building complex agents.
- Programming-like flexibility: Supports variables, branching, loops, subflows, and other logic, giving sophisticated control over agent workflows.
- Multiple AI model support: Integrate with OpenAI, Anthropic, or other AI models as needed for different steps.
- Robust error handling & debugging tools: Designed with developers in mind, it offers logs and debug options to fine-tune workflows.
Cons ❌
- Steeper learning curve: The rich functionality means it can feel complex for new users – there’s a lot to learn before mastering it.
- More complex setup: Initial agent creation might require careful planning; not as plug-and-play as simpler tools.
- Requires some technical mindset: Even though it’s no-code, you benefit from understanding programming logic to use it effectively.
- Pricing is higher: Gumloop is positioned for business use and their basic plan cost $97/mo.
Pricing 💰
- Free Tier: Yes – 100 credits / month.
- Starter: $97/month (generous for single users or small teams).
- Pro: $297/month (higher capacity and collaboration).
- Enterprise: Custom pricing for large organizations.
Takeaway: Gumloop is terrific for those who need powerful AI automation without coding. Users love its flexibility. However, if you’re not willing to invest time learning its features, it might be overkill. It’s best suited for power users who demand flexibility and are okay with a bit of complexity to get there.
3. Lindy.ai
⭐ G2: New platform (limited reviews)
Best for: AI assistants for managing human-like workflows and daily tasks.

Lindy.ai is an AI assistant platform that lets you create agents to help with everyday business tasks (think of it like a supercharged virtual assistant). Lindy’s focus is on automation of routine tasks such as email management, scheduling meetings, CRM data entry, note-taking, and more, using natural language. You can instruct Lindy agents in plain English and connect them to your apps (it boasts support for hundreds of app integrations like Gmail, Calendar, Slack, HubSpot, etc.). The platform emphasizes being AI-first and extremely accessible – you can build an agent in minutes to, say, handle your inbox triage or update spreadsheets based on incoming data, without writing any code.
Pros ✅
- Natural language interface: You can set up and interact with agents using everyday language, which makes task management very intuitive.
- Great for routine tasks: Designed to offload repetitive daily chores (inbox zero, meeting follow-ups, data entry), freeing up your time for more important work.
- Model-agnostic with easy switching: It uses large language models under the hood and may allow switching between providers for different tasks (e.g., GPT-4 vs others).
Cons ❌
- Unpredictable due to heavy reliance on AI: As one reviewer noted, if you automate heavily, you must be careful not to reduce necessary human oversight (e.g., always double-check important communications the AI drafts).
- Less advanced workflow logic: Compared to some competitors, Lindy’s workflow customization is more straightforward – it may lack complex branching or looping for truly complex scenarios.
- Custom AI behavior requires prompt writing: To tailor an agent’s actions, you often have to write out instructions or examples (prompts) for the AI, which can be a bit of trial-and-error if you’re not used to prompt engineering.
Pricing 💰
- Free Tier: Yes – e.g. ~400 tasks per month and a basic knowledge base included for free to get started.
- Pro: Starts at $29.99/month, which includes a generous number of tasks (around 3,000 tasks/month).
- Enterprise: Custom pricing for organizations with higher volume or additional needs (likely includes dedicated support, more integrations, etc.).
Takeaway: Lindy.ai stands out as a versatile personal AI assistant that’s easy to set up. It’s ideal if you want to automate everyday chores without dealing with technical complexity. Early users love its comprehensive automation capabilities across email, support, scheduling, etc., and especially praise how user-friendly and fast it is to create agents using natural language.
4. Relevance.ai
⭐ G2: 4.4 (out of 5 stars)
Best for: Custom AI agents with rich data integration and vector search capabilities.

Relevance.ai is a platform for building AI-powered applications and agents, notable for its emphasis on vector embeddings and unstructured data analysis. It provides a no-code interface for designing AI agents (sometimes called an “AI workforce”) that can be taught to carry out tasks on autopilotg2.com. You can integrate multiple AI models and connect the agents to your data via vector search, meaning the agents can have a form of memory or knowledge base. Typical use cases for Relevance.ai include creating custom AI chatbots that draw on your company’s documents, automating support tickets by understanding context, or any scenario where you need an AI to learn from your data and perform tasks. It’s aimed at ops teams and subject-matter experts – people who know their processes, even if they aren’t coders, can train up AI agents to execute those processes.
Pros ✅
- Custom AI agent creation: Design your own agents and even teams of agents to work together on tasks – e.g., one agent extracts info, another summarizes, etc.
- Analytics & monitoring: Offers tools to track agent performance and outcomes, which is important for refining your automations.
- Knowledge base integration: You can feed your own data to agents (via vector databases), so they can make decisions based on your specific information.
Cons ❌
- Expensive pricing at scale: One common complaint is that Relevance.ai can get pricey, with many advanced features only in higher-tier plans. Running multiple agents or large volumes might strain a budget.
- Needs better onboarding guides: Users have noted that the platform could offer more in-depth tutorials and guides for newcomers. The initial learning curve could be improved with better documentation.
- Customer support issues: Some reviewers mention slow or lacking support responses, which can be frustrating if you hit a roadblock.
- Complex setup for advanced use: While basic agent building is straightforward, implementing more complex, enterprise-grade processes might require significant configuration and expertise.
- Integration options still growing: It may not have the breadth of third-party app integrations that a tool like Zapier has, potentially requiring API work for certain connections.
Pricing 💰
- Free: Yes – 100 credits / day.
- Pro: $19/mo - 10,000 credits / month.
- Team: $199/month – for moderate usage, likely includes more agents and higher data limits.
- Business: $599/month – for larger scale deployments and more advanced features.
- Enterprise: Contact for pricing – custom plans with maximum capacity, dedicated support, and on-prem options if needed.
Takeaway: Relevance.ai provides a robust and versatile AI agent platform, especially if your agents need to work with your own data and deliver insights. Users love its ease of use and powerful data handling. But keep an eye on cost and be prepared to invest in learning the platform to unlock its full potential. If you find Relevance.ai doesn’t meet a particular need (or budget), the alternatives on this list like Relay.app or Stack AI might fill the gap, which is why people often compare these platforms.
5. Zapier
⭐ G2: 4.5 (1,300+ reviews)
Best for: Integrating AI agents with thousands of existing apps and workflows.

Zapier is a very well-known automation tool (the “OG” of no-code workflows) that has recently added AI agent-building features. Traditionally, Zapier connects your apps: “When X happens in app A, do Y in app B.” Now, with Zapier’s AI integrations (like the Zapier Natural Language Actions and built-in OpenAI integration), you can include AI steps in those automations. Zapier isn’t an AI-specialized platform like some others here, but its strength is the 7,000+ app integrations it supports. This means you can trigger AI agents based on almost any event (new email, form submission, CRM update—you name it) and then have the AI perform an action or generate content as part of the workflow. Use cases: e.g., automatically summarize every new support ticket with GPT and post it to Slack, or generate a draft email reply when a lead comes in, etc., all using Zapier’s easy workflow editor.
Pros ✅
- Massive integration ecosystem: Zapier connects with over 7,000 apps, so your AI agent can interact with nearly any tool your business uses. This is unmatched in the industry.
- Mature product and platform: Zapier is a mature platform with a reputation for dependable execution of workflows and extensive documentation + community support.
- Extensive template library: There are thousands of pre-built Zap templates (including some with AI) to get you started quickly.
Cons ❌
- AI agent capabilities not as advanced: Zapier’s AI functions are relatively basic compared to specialized AI agent builders. It can call an AI to do a task (like “run this prompt”), but it lacks the richer multi-step AI logic or memory that others provide.
- Higher pricing for heavy use: Zapier can become expensive if you have a lot of tasks (each workflow run counts as a task). Adding AI steps might use more tasks/credits, and the higher plans get pricey.
- Limited multi-agent orchestration: It’s mostly linear workflows. If you envision agents collaborating or complex branching, Zapier alone might not suffice.
Pricing 💰
- Free Tier: Yes – the Free plan allows 100 tasks/month and single-step Zaps(enough to try out basic automations).
- Starter: $19.99/month – 750 tasks and multi-step Zaps, no AI included by default but you can use your own OpenAI key.
- Professional: $49/month – higher task count, advanced features (like conditional logic).
- Team: $69/month – collaboration features and even more tasks.
- Company: $125/month and up – for enterprise needs (massive volume, SSO, etc.).
Takeaway: If you already use Zapier for automation, it’s a natural step to experiment with its AI features. It’s best for scenarios where connecting different apps is the priority, and AI just plays one part in the workflow. For instance, automating across Salesforce, Gmail, and Slack with an AI summary in between – Zapier is perfect for that. However, if your goal is a standalone intelligent agent with complex reasoning or multi-turn interactions, Zapier might feel limited. Many users pair Zapier with other AI-centric platforms (or use Zapier to trigger those) to get the best of both worlds.
6. n8n
⭐ G2: 4.6 (50+ reviews)
Best for: Self-hosted AI agent implementation with full customization.

n8n is an open-source workflow automation tool, much like a self-hostable alternative to Zapier, that you can also extend to build AI agents. It provides a node-based editor to connect different services and logic. With n8n, you have the freedom to host it on your own server (for free, if self-hosted) and even modify the code. For AI capabilities, n8n doesn’t come with built-in AI like others, but you can use API calls (e.g., to OpenAI, HuggingFace) or community-contributed nodes to integrate AI into your flows. This means you can create automations where, say, a webhook triggers a series of actions and one action calls an AI model for processing, then continues the flow. It’s incredibly flexible and a favorite for developers who want full control over their automation/agent logic without vendor lock-in.
Pros ✅
- Open-source platform: n8n’s code is open, giving you transparency and the ability to run it independently (great for privacy and cost control).
- Self-hosting option: You can run n8n on your own server or cloud – no forced cloud service fees, and you keep your data in-house.
- Extensive customization: Because you have the code, you can create custom nodes or integrate with any API. You’re not limited by what the provider offersrelay.app.
- Active community: There’s a vibrant community contributing new integrations (nodes) and helping on the forums. Many share how to use n8n for AI tasks.
- Flexible integration options: n8n supports a broad set of integrations (though not as many as Zapier) and you can connect to any REST API, which effectively means endless possibilities.
- Cost savings at scale: High-volume tasks won’t necessarily cost more if you run it on your own infrastructure, unlike per-task pricing models.
Cons ❌
- Requires significant technical expertise: Let’s be clear – n8n is developer-friendly, which means non-technical users may struggle. Setting up a server, managing it, and creating flows in n8n often requires understanding APIs and JSON, etc.
- Complex setup process: Initial installation (if self-hosting) and maintenance (backups, updates) is on you. There is a cloud offering, but that comes at a cost and somewhat negates the self-hosting benefit.
- More maintenance: Using any self-hosted tool means you handle uptime, scaling, and troubleshooting issues – tasks a SaaS would normally do for you.
- License considerations: (For completeness: n8n’s community edition is open-source under a fair-code license, which restricts reselling the service. This only matters if you plan to embed it in a commercial product.)
- UI less polished: The interface, while functional, may not be as slick or intuitive as some commercial products, which could steepen the learning curve for building workflows.
Pricing 💰
- Open-Source Self-Hosted: Free. You can run n8n on your own server at no license cost.
- n8n Cloud: Starts at €20/month (around $22) for the Starter plan, which offers hosted n8n with a certain number of workflow executions and support. Higher tiers (Business, Enterprise) are custom priced for more executions and enterprise features.
Takeaway: n8n is a powerhouse for those who need complete control and on-premise capability. It’s like having your own Zapier that you can bend to your will – and integrate AI wherever you want by calling AI APIs. If you’re a developer or have access to one, and are concerned about data privacy or costs of SaaS tools, n8n is extremely compelling. However, if you don’t want to deal with technical details, a cloud-based builder like Relay.app or Lindy.ai will get you results much faster and more easily. For open-source enthusiasts looking to include AI in their automation, n8n (possibly combined with something like Flowise for the AI part) is a top choice.
7. CrewAI
⭐ G2: N/A (Emerging platform) – Best for: Multi-agent orchestration and complex team-of-AI scenarios.

CrewAI is a cutting-edge framework and platform for orchestrating autonomous AI agents working in teams. Inspired by the concept of “agent swarms,” CrewAI lets you create a group (a “crew”) of AI agents, each with specific roles and tools, that can collaborate to tackle complex tasks together. For example, one agent might research data, another writes a report, and another checks for errors, all within one workflow. CrewAI provides both an open-source Python framework for developers and a no-code Studio UI for non-coders to build these multi-agent automations. You can use any Large Language Model (LLM) – OpenAI, Anthropic, local models, etc. – for your agents, and integrate with various cloud platforms and tools. Use cases include advanced process automation like incident response (one agent gathers logs, another analyzes, another writes a summary), complex content generation pipelines, or any scenario where splitting tasks among specialized AI agents could be more efficient than one monolithic agent.
Pros ✅
- Multi-Agent Automation: CrewAI is built from the ground up to support multiple agents working simultaneously, something most other platforms don’t natively offer. This can solve tasks that one agent alone might struggle with.
- User-friendly interface (Studio): Despite dealing with multi-agent complexity, the platform offers a straightforward visual interface for building your agent teams, making it as easy as drag-and-drop to define roles and flows.
- Scalability: It’s designed to scale from small projects to large enterprise workflows. You can deploy many agents and run them in parallel, suitable for big automation tasks
Cons ❌
- Initial learning curve: The concept of multi-agent systems is new and can be hard to grasp at first. New users might need time (and good examples) to fully understand how to best utilize multiple agents together.
- Limited third-party integrations (for now): CrewAI is focused on the agents themselves; it currently supports a select number of integrations out-of-the-box. It may not yet match the breadth of integrations of more mature automation tools, requiring custom work for some connections.
Pricing 💰
- Free Tier: Yes – CrewAI offers a free tier to explore its features (and of course the core framework is open source, which you can use without charge).
- Pro Tier: Starts at $49.99/month for advanced features and support. This likely includes higher usage limits and premium tools like CrewAI+ for API hosting.
- Enterprise: Custom pricing for large-scale deployments, with options for on-premise, dedicated support, and more. (You’d contact CrewAI for specifics.)
Takeaway: CrewAI is one of the most innovative entrants in the AI agent space, enabling scenarios that others simply can’t do (multiple agents working together). It’s gaining popularity, and even partnerships with big players like Nvidia suggest it’s pushing the envelope in AI capabilities. For organizations looking to automate very complex workflows or experiment with agent collaboration, CrewAI is a superb choice. Just be prepared to invest some time into understanding multi-agent design. If you’re a beginner, you might start with a single-agent platform like Relay.app, and graduate to CrewAI when you have a grasp of what multiple agents could achieve for you.
8. Flowise
⭐ G2: N/A (Open-source community tool)
Best for: Building LLM-powered agents and chatbots with a low-code, visual builder (developer-friendly).
[Image 9: Flowise interface]
Flowise is an open-source low-code platform that makes it easy to build custom LLM (Large Language Model) applications and AI agents. Think of Flowise as a visual builder for AI workflows: you can drag and drop components to connect an LLM (like GPT-4 or open-source models) with various tools (data sources, memory, APIs). It’s often compared to LangChain, but with a no-code UI on top. With Flowise, you can create chatbots, question-answering agents over documents, or agents that use tools (like web search or calculators) in their reasoning. It supports many integrations, including LangChain and LlamaIndex, and over 100+ other services for inputs/outputs. Flowise is great for developers who want to prototype and deploy AI agents quickly, or anyone who wants the flexibility of custom AI logic without writing a lot of boilerplate code. Since it’s open-source, you can self-host it and even embed it into your own applications.
Pros ✅
- Drag-and-drop UI for LLMs: Flowise provides a user-friendly visual interface to construct complex LLM flows, significantly reducing the coding needed. This lowers the learning curve for creating AI agents that might use memory, external tools, etc.
- Open-source and extensible: It’s free to use and you can extend it. Being open-source means a community contributes new nodes/integrations, and you’re not locked in – you can modify or self-host as you wish.
- Quick iteration for developers: You can test your agent flows in the UI and iterate rapidly, which is faster than writing code and debugging for each change. Great for prototyping
- Run locally or on cloud: You can run Flowise on your local machine for quick experiments or deploy it on a server/VM for production use. No need to rely on a third-party service if you don’t want to.
Cons ❌
- Technical setup for self-hosting: To use Flowise, you need to install and run it (Node.js based). While not very hard for a developer (a couple of commands), it’s still a barrier for non-technical folks. There is a hosted option, but that introduces cost.
- Learning curve for advanced features: Building a simple chatbot is straightforward, but to fully leverage Flowise (using memory modules, tool integrations, custom actions), you’ll need some understanding of how LLMs and LangChain-style agents work. Beginners might need to spend time learning concepts of prompts, memory windows, etc.
- Less polished than commercial tools: The UI/UX, while good, may not be as slick as a paid product. Documentation might not be as comprehensive as something like Zapier’s, though it’s improving.
Pricing 💰
- Open Source Version: Free. You run it yourself, and the only costs are your compute (and any API costs for AI models you use).
- Hosted Cloud: Flowise offers a cloud service with a 14-day free trial. After that: Starter is $35/month, Pro $65/month, which include certain numbers of predictions and features, and an Enterprise plan for larger needs. (These plans save you the trouble of hosting and come with support).
Takeaway: Flowise is a fantastic option for those who want the flexibility of custom AI agents without building from scratch. It’s like getting under the hood of how AI agents work, but with a friendlier interface. If you have some technical inclination and desire to build something unique (say, a chatbot that references your own database, or an AI agent that calls APIs to get its job done), Flowise gives you the tools to do it quickly. On the other hand, if you just want a plug-and-play solution and don’t care to customize deeply, you might lean toward a managed platform. Many users even use Flowise in conjunction with others: for example, using n8n or Zapier to handle non-AI automation, and Flowise to handle the AI decision-making part of the workflow. The good news is it’s free to try, so it’s worth experimenting with to see the power of building AI agents visually.
9. Stack AI
⭐ G2: 4.3 (3 reviews)
Best for: Enterprise AI agent deployment with comprehensive analytics and governance.

Stack AI is a platform geared towards enterprises that want to build and deploy AI agents with an emphasis on security, monitoring, and integration in a corporate environment. It allows companies to design AI agents that can automate business processes, similar to others, but the key selling points of Stack AI are its robust analytics, audit logs, and security controls. In other words, it not only lets you create the agents, but also keep a close eye on what they’re doing, how they’re performing, and ensure they’re compliant with organizational policies. Use cases for Stack AI typically involve more sensitive or mission-critical processes – e.g., automating parts of customer support, running internal knowledge base Q&A agents for employees, or handling data processing tasks – where the company needs to track agent decisions and maintain an audit trail. Stack AI likely integrates with enterprise software and databases, providing a layer for AI automation that meets IT governance standards.
Pros ✅
- Enterprise-grade features: Things like version control for agent configurations, testing sandboxes, multi-user collaboration with permissions, etc., are likely part of the platform.
- Advanced deployment options: You might be able to deploy Stack AI agents in various environments (cloud, on-prem, hybrid) to meet IT requirements. This flexibility is good for fitting into existing infrastructure.
- Knowledge base integration: It has good support for connecting to corporate knowledge bases or databases, so agents can use the company’s data effectively.
Cons ❌
- Complex interface: Given all the features, the UI can be dense. New users may find it not as immediately intuitive as simpler tools. Training might be needed to use it effectively.
- Steeper learning curve: It’s aimed at power users in an organization, so there may be an assumption you have some background in automation or AI concepts. Not as friendly for absolute beginners.
- Higher pricing for advanced features: Stack AI is likely on the pricier side, especially for full-feature enterprise use. Its Starter and Team plans (if any) are relatively expensive, reflecting its business focus. Small businesses or hobbyists might find it cost-prohibitive.
Pricing 💰
- Free Tier: Yes – Stack AI appears to have a free tier for limited use, e.g., 100 runs per month which is likely for trial or very light usage.
- Starter: ~$139/month – aimed at small teams or pilot projects, with a moderate limit on agent runs and features.
- Team: ~$699/month – aimed at larger teams or departments, with higher limits and more enterprise features enabled.
- Enterprise: Custom pricing – for organization-wide deployment with all features, custom support, and SLAs.
Takeaway: Stack AI is built for the enterprise environment, meaning it’s less about shiny AI tricks and more about reliability, oversight, and integration into business processes. If you are in a large company and need to deploy AI agents that your IT department will approve of, Stack AI should be on your shortlist. It ensures that as you embrace AI automation, you’re not sacrificing on compliance or observability. Companies that have strict rules (finance, healthcare, etc.) will appreciate features like audit logs and security controls. On the flip side, if you’re just an individual or small startup hacking together an AI bot, Stack AI will probably be overkill (and too expensive). In summary: great for enterprise, but probably not aimed at casual users.
10. Agent.ai
⭐ G2: New platform (500k+ users, not yet rated)
Best for: Community-driven AI agent marketplace and simple low-code agent builder.
[Image 11: Agent.ai interface]
Agent.ai is a unique entry on this list. Rather than being a pure tool for you to build agents from scratch, it’s described as “the #1 professional network for AI agents” – essentially a marketplace and community for AI agents created by users (the “Agent Network”), combined with an Agent Builder that lets you create and publish your own agents.
Launched in late 2024 by HubSpot’s founder Dharmesh Shah, Agent.ai exploded in growth, reaching over 500,000 users in just a few months. The idea is that you can find pre-built AI agents for various use cases (customer service, sales outreach, marketing, etc.) contributed by others, test them out, and even rate them. If you have a specific need, you can use the low-code Agent Builder to create your own agent and even share it on the network. Agents on the platform might chain together multiple AI actions or integrate with business apps (given the HubSpot influence, likely CRM and marketing tools). For example, you might discover an agent that automatically responds to common customer emails with AI, or one that generates social media posts from blog content. Agent.ai blends a consumer-friendly approach (browse and deploy agents easily) with the ability to tweak or build agents without heavy coding.
Pros ✅
- Large library of pre-built agents: Since many users contribute, you have a variety of ready-made agents to choose from. Instead of building from scratch, you might find one that fits your needs (or close to it) and adapt it.
- Rapid community-driven iteration: With thousands of users and agents, the best agents get upvoted and reviewed, helping you identify what works (13,000+ ratings were submitted on agents by early 2025)cxtoday.com. This crowdsourcing of innovation means new useful agents appear all the time.
- Low-code Agent Builder: For creating your own, Agent.ai provides a simple builder interface so you don’t need to be a developer to program an agent’s behaviorcxtoday.com. It likely involves configuring triggers and AI actions (similar in spirit to Zapier or Relay). 5,000+ people have already used the builder to make custom agentscxtoday.com.
Cons ❌
- Quality varies across agents: Since anyone can publish agents, not all will be high quality. You might need to sift through or test a few to find the ones that truly work for you (community ratings help mitigate this).
- Limited customization depth: The builder is low-code, which is great for ease, but if you want to create highly complex logic, you might hit limitations. It’s designed for simplicity, so advanced users might find it lacks some power features.
- Integration scope not clear yet: It’s not obvious which external apps Agent.ai can connect with at this point. It likely has some focus (HubSpot CRM integration would be logical), but it may not have the extensive integration list of something like Zapier yet.
Pricing 💰
Agent.ai has not publicly detailed pricing. Currently, it appears to be free to sign up and use agents on the network (possibly to gather users and feedback). In the future, they might monetize by offering premium agents, a subscription for unlimited agent usage, or enterprise packages (especially if it integrates with tools like HubSpot’s CRM). For now, you can likely experiment without a cost, aside from any services the agents themselves might use (for example, if an agent uses OpenAI’s API, that might require an API key or have some cost, but the platform might be covering that in beta).
Takeaway: Agent.ai represents a new wave of AI agent platforms that leverage community and sharing. It’s almost like an App Store for AI agents – which is great because you can quickly find solutions to common problems and you’re not reinventing the wheel. For beginners, this is extremely appealing: you might find an agent that does exactly what you need with one click. And if not, the builder is there to help you create one easily. Keep in mind it’s early-stage; if you’re risk-averse, you might wait for it to mature a bit. But given its explosive growth and the backing of a well-known founder, Agent.ai is definitely a platform to watch (and try out) in the AI agent space.
Making Your Choice 🚦
With a lineup of AI agent builders ranging from no-code simplicity to open-source power, how do you choose the right one? Here are some key considerations to help you decide:
- Ease of Use: If you need a platform that anyone on your team can use, Relay.app stands out as the most user-friendly option. It’s perfect for beginners and still powerful enough as you grow. Agent.ai is also very easy for quick solutions, but it’s newer.
- Agent Complexity: Consider what tasks you want your AI agents to perform. For straightforward workflows (send an email, update a spreadsheet with AI-generated text), a simpler tool is fine. For very complex, multi-step reasoning or multi-agent collaboration, look to Gumloop (advanced logic) or CrewAI (multi-agent crews) which provide the flexibility needed.
- Integration Needs: Evaluate how well each platform connects with your existing tools. If you require a wide array of integrations (connecting to many SaaS apps), Zapier (and its cousin Make.com) are integration kings, though Relay.app and Lindy.ai also support many popular apps. For more niche or self-hosted integrations, n8n or Flowise might be better since you can create your own connectors.
- Technical Expertise: Be honest about your (or your team’s) capabilities. If you don’t have coding skills available, stick with no-code platforms like Relay.app, Lindy.ai, or Agent.ai. If you have developers excited to tinker, open-source options like n8n or Flowise will let them deeply customize the solutionrelay.app.
- Deployment and Control: If you require on-premise hosting for compliance, rule out fully hosted-only solutions. n8n, Flowise, or an enterprise plan of Stack AI might be necessary. If cloud is fine, then any of the SaaS platforms will do.
- Cost: Start with your budget. Some platforms have generous free tiers (Relay.app’s free plan is quite robust; Agent.ai is free at the moment; Flowise open-source is free) which can be great for pilot projects. Others like Zapier or Stack AI can become expensive as you scale. Consider not just current costs but how pricing will scale with usage – e.g., per-task costs, or limits on runs, etc. Always align the choice with the potential ROI of the automation.
In conclusion, the best AI agent builder for you is the one that matches your use case and skill level. If you’re just starting out and want quick wins, Relay.app is a fantastic first choice due to its ease of use and strong all-around capabilities (it’s often praised as a top modern tool with a great user experience. As your needs grow, you might incorporate other tools – for instance, using Relay for core workflows, and maybe experimenting with CrewAI for a specialized multi-agent project, or Flowise for a custom LLM-based chatbot. The good news is you’re not limited to one: many of these can complement each other.