# Activepieces vs AgentRunner

Activepieces records 258,553 monthly visits with +1.5% month-over-month growth and Freemium pricing. AgentRunner records 0 monthly visits with 0% growth and Freemium, Free pricing.

| Metric | [Activepieces](https://openaitools.app/tool/activepieces) | [AgentRunner](https://openaitools.app/tool/agentrunner) |
| :--- | :--- | :--- |
| Website URL | https://www.activepieces.com | https://agentrunner.com |
| Categories | AI Workflow, No-Code&Low-Code, AI Code Assistant, AI Agent | AI Workflow, AI App Builder, AI Agent, AI Developer Tools |
| Pricing Model | Freemium | Freemium, Free |
| Monthly Visits | 258,553 | 0 |
| MoM Growth Rate | +1.5% | 0% |
| Primary Market | United States | Global |
| Direct Visits | 111,328 | 0 |
| Review Score | 4.6 | 4.3 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## Activepieces

Activepieces is an AI-first automation platform built around the idea that a team's agents and its people should share one workspace. At the center are AI agents: you describe a job in plain words and the agent works out the steps, the order and which tools to open across your connected apps and any MCP server you point it at. Sensitive steps can be gated behind human approval, so money, customer and production actions stay under control.

Underneath the agent layer sits a mature workflow engine with a visual builder. Chat can draft most of a flow, while branching, retries, waitpoints, subflows, error handling and human approvals handle the hard cases. Where a step needs real logic, you can drop into inline TypeScript and keep the rest visual. Chat, Tables (a lightweight structured data layer), a knowledge base and an MCP server round out the platform so agents and teammates operate on the same data.

The project is open source at its core, with hundreds of contributors maintaining MIT-licensed app pieces, and it deploys flexibly: Activepieces Cloud, your own Docker or Kubernetes infrastructure, or a fully air-gapped install. Enterprise controls include projects and access roles, SSO via Okta or Entra, secret managers such as HashiCorp Vault, audit logs streamed to your SIEM, and bring-your-own AI model keys from Anthropic, OpenAI, AWS Bedrock or Google Gemini.

**Pricing & Plans:** Freemium model: a free plan requiring no credit card lets you start building flows and agents, with paid plans for higher run volumes and enterprise features. Deployment options range from the managed cloud to self-hosted and air-gapped, and open-source users can run the community edition on their own infrastructure.

- **AI agents from plain language:** Describe a task in everyday words and the agent determines the steps, chooses tools from your connected apps and MCP servers, and pauses for approval on sensitive actions.
- **Visual flow builder with inline TypeScript:** Build automations on a canvas with branching, retries, waitpoints, subflows and error handling, then write inline TypeScript for the steps that need real code.
- **770+ open-source app connectors:** Every piece is MIT-licensed and community-built, covering the apps you already run, with an HTTP piece for any REST or GraphQL endpoint with auth and pagination handled.
- **Chat, Tables and knowledge base:** Draft flows by chatting, store structured data in Tables that flows and agents can read and write, and keep internal documents searchable by every agent.
- **Enterprise deployment and governance:** Run on the managed cloud, your Docker/Kubernetes stack or air-gapped, with projects, SSO, role-based access, secret managers, audit logs and bring-your-own AI keys.

**Strengths:** Open-source core with MIT-licensed pieces and a genuinely self-hostable build; Strong blend of AI agents, a visual builder and inline TypeScript; Enterprise-grade controls including SSO, roles, secret managers and audit streaming; Large connector library plus an HTTP piece for anything not covered

**Limitations:** The breadth of agents, tables, flows and MCP features can overwhelm new users; Some advanced enterprise capabilities are reserved for paid and self-managed plans; Self-hosting means you own upgrades, scaling and reliability

[Profile (Markdown)](https://openaitools.app/tool/activepieces.md)

## AgentRunner

AgentRunner is a no-code visual development environment for teams that build with large language models. Instead of juggling prompts across notebooks, scripts and documentation, you keep every prompt inside one workspace and chain them together on a node-based canvas. Each node can call a model, transform the data returned, or hand off to an external API, which makes it practical to describe a multi-step AI application as a diagram rather than a pile of glue code.

The platform is aimed at developers, prompt engineers and product teams who want to prototype fast and then measure results. Prompt versioning and call logging let you compare how different phrasings behave before you commit to one, and native integrations with providers such as OpenAI, Claude and LLaMa mean you can route different stages of the same workflow to different models. Typical outcomes include customer-support chatbots, content generation pipelines and automation of routine internal decisions.

AgentRunner is presented by a team with previous product experience (the creators of SAAS First and MillionVerifier) and positions its deployment layer as a planned, product-led step for taking prototypes to production. Because the builder targets people comfortable wiring APIs together, it sits somewhere between pure no-code tools and a traditional development stack.

**Pricing & Plans:** AgentRunner advertises free and freemium access, with paid or contact-based arrangements for teams that want to deploy or embed the workflow builder. Specific plan limits and per-seat pricing are not published on the public pages we reviewed, so treat the listed tiers as directional and confirm current terms directly with the vendor.

- **Visual node-based workflow editor:** Design complex AI applications by chaining prompt nodes, manipulating data between them and wiring in external APIs — all on a drag-and-drop canvas.
- **Centralized prompt management:** Edit, organise and version every prompt from a single workspace instead of scattering them across code files and notebooks.
- **Multi-model integration:** Connect accounts for models from OpenAI, Claude, LLaMa and other providers, letting you compare and route between them inside one workflow.
- **Prompt testing and logging:** Test, log and track AI calls so you can measure which prompt version performs best and iterate toward a stronger assistant.
- **Deployment path for AI apps:** Move from a working prototype to a launched application with a product-led flow built for shipping rather than demoing.

**Strengths:** Node-based canvas makes complex multi-step prompt chains readable at a glance; Centralised prompt storage with versioning and call logging aids real iteration; Connects to multiple model providers, so you are not locked into a single vendor; Built by a team with prior SaaS product experience, aiming at production deployment

[Profile (Markdown)](https://openaitools.app/tool/agentrunner.md)

## Frequently Asked Questions

### How do Activepieces and AgentRunner compare in monthly traffic?

Activepieces has 258,553 monthly visits, while AgentRunner has 0. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Activepieces has a month-over-month growth rate of +1.5%; AgentRunner has 0%.

### How does pricing compare?

Activepieces: Freemium. Freemium model: a free plan requiring no credit card lets you start building flows and agents, with paid plans for higher run volumes and enterprise features. Deployment options range from the managed cloud to self-hosted and air-gapped, and open-source users can run the community edition on their own infrastructure. AgentRunner: Freemium, Free. AgentRunner advertises free and freemium access, with paid or contact-based arrangements for teams that want to deploy or embed the workflow builder. Specific plan limits and per-seat pricing are not published on the public pages we reviewed, so treat the listed tiers as directional and confirm current terms directly with the vendor.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Base44](https://openaitools.app/tool/base44) | 14,039,232 | +0.5% | Freemium, Paid, Contact for Pricing | Build working apps, websites, and AI agents by describing them | [.md](https://openaitools.app/tool/base44.md) |
| 2 | [Zapier](https://openaitools.app/tool/zapier-com) | 5,065,248 | +0.4% | Freemium, Free Trial, Paid | Automate work across thousands of apps — no code required | [.md](https://openaitools.app/tool/zapier-com.md) |
| 3 | [n8n](https://openaitools.app/tool/n8n) | 4,522,449 | -7.4% | Freemium | Open-source workflow automation built for AI agents and technical teams | [.md](https://openaitools.app/tool/n8n.md) |
| 4 | [MindStudio](https://openaitools.app/tool/mindstudio) | 1,793,337 | +14.2% | Contact for Pricing | No-code builder for custom AI agents and workflows | [.md](https://openaitools.app/tool/mindstudio.md) |
| 5 | [Dify](https://openaitools.app/tool/dify-ai) | 819,691 | -15% | Freemium | Build, deploy, and govern production-ready agentic AI workflows | [.md](https://openaitools.app/tool/dify-ai.md) |
| 6 | [Gumloop](https://openaitools.app/tool/gumloop) | 379,557 | -21.1% | Freemium, Paid, Contact for Pricing | Excellent browser and web scraping automation features for AI agents, but fewer standard enterprise app integrations. | [.md](https://openaitools.app/tool/gumloop.md) |
| 7 | [Tines](https://openaitools.app/tool/tines) | 273,260 | +24.4% | Freemium, Contact for Pricing | A secure environment where teams build, deploy and govern AI agents, apps and automations | [.md](https://openaitools.app/tool/tines.md) |
| 8 | [Relevance AI](https://openaitools.app/tool/relevance-ai) | 192,083 | -15.5% | Free Trial, Contact for Pricing | Advanced multi-agent workforce builder for complex tasks, but less suited for traditional webhook integrations. | [.md](https://openaitools.app/tool/relevance-ai.md) |
| 9 | [FlowHunt](https://openaitools.app/tool/flowhunt-io) | 186,190 | 0% | Free Trial, Paid | No-code AI agents and chatbots for marketing, SEO and support | [.md](https://openaitools.app/tool/flowhunt-io.md) |
| 10 | [Coze](https://openaitools.app/tool/coze) | 177,539 | -33.3% | Freemium | Strong multi-channel publishing capabilities for AI agents, but less comprehensive for multi-step backend data pipelines. | [.md](https://openaitools.app/tool/coze.md) |

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Source: https://openaitools.app/compare/activepieces-vs-agentrunner

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