# Activepieces vs Alloy

Activepieces records 258,553 monthly visits with +1.5% month-over-month growth and Freemium pricing. Alloy records 76,711 monthly visits with -33.6% growth and Freemium pricing.

| Metric | [Activepieces](https://openaitools.app/tool/activepieces) | [Alloy](https://openaitools.app/tool/alloy) |
| :--- | :--- | :--- |
| Website URL | https://www.activepieces.com | https://alloy.app |
| Categories | AI Workflow, No-Code&Low-Code, AI Code Assistant, AI Agent | AI Workflow |
| Pricing Model | Freemium | Freemium |
| Monthly Visits | 258,553 | 76,711 |
| MoM Growth Rate | +1.5% | -33.6% |
| Primary Market | United States | United States |
| Direct Visits | 111,328 | 30,976 |
| Review Score | 4.6 | 4.2 |
| 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)

## Alloy

Alloy flips the usual prototype workflow. Rather than starting from a blank canvas or a screenshot, you point it at the product you already ship. A browser extension captures pages with no setup, while connecting the codebase lets Alloy run the app in a sandbox and produce changes that are closer to production code. From there, prompting is conversational: describe a change, watch it render live, and keep iterating.

Because every session lives in the cloud, teammates and even customers can open a link and comment without installing a local developer environment. Sessions can also be kicked off from Slack and run in parallel. When a prototype is settled, Alloy can export it, expose it over MCP, or turn it into a GitHub Pull Request, which shortens the handoff step that normally slows product work down.

Alloy also fits into the surrounding tool stack: integrations pull insights and customer requests from other systems, Figma import and export keeps design teams in the loop, and you can route prompts through your own Claude or ChatGPT subscription instead of burning Alloy credits on supported models.

**Pricing & Plans:** Freemium model. There is a free starting tier, paid plans (Pro workspaces unlock things such as Figma import), and an Enterprise offering. Exact prices vary by plan, so check the pricing page before budgeting.

- **Prototype from your real product:** Use a no-setup browser extension to capture live pages, or connect your codebase so Alloy runs your app in a sandbox and writes code that fits your stack.
- **Design-system aware output:** Upload your library so the agent builds with your real components, tokens, and assets instead of producing off-brand screens.
- **Cloud sessions and instant sharing:** Every session runs in the cloud; share a link so teammates or customers can view, comment, and give feedback without local setup.
- **Figma import and export:** Pull a Figma frame into Alloy as a working prototype, then send prototype screens back into a Figma Design file.
- **Push to a Pull Request:** Convert a finished session into a GitHub Pull Request, or access it through MCP, to move from idea to shipped change faster.

**Strengths:** Works from your real product, codebase, and design system rather than generic templates; Cloud sessions and links remove local environment setup for non-engineers; Clear path from prototype to production via GitHub Pull Requests and MCP; Can use your own Claude or ChatGPT subscription for supported models

**Limitations:** Connecting a codebase requires admin permissions and roughly 15 minutes of setup; Figma Make files are not supported yet, and some capabilities are gated to Pro workspaces; Value depends heavily on having an existing product to prototype against

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

## Frequently Asked Questions

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

Activepieces has 258,553 monthly visits, while Alloy has 76,711. 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%; Alloy has -33.6%.

### 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. Alloy: Freemium. Freemium model. There is a free starting tier, paid plans (Pro workspaces unlock things such as Figma import), and an Enterprise offering. Exact prices vary by plan, so check the pricing page before budgeting.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [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) |
| 2 | [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) |
| 3 | [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) |
| 4 | [Dify](https://openaitools.app/tool/dify-ai) | 819,691 | -15% | Freemium | Stronger focus on RAG knowledge bases and LLM application development, but less general business automation. | [.md](https://openaitools.app/tool/dify-ai.md) |
| 5 | [UX Pilot](https://openaitools.app/tool/ux-pilot) | 537,999 | +2.9% | Freemium | From idea or sketch to editable wireframes, hi-fi UI and code in minutes | [.md](https://openaitools.app/tool/ux-pilot.md) |
| 6 | [Gumloop](https://openaitools.app/tool/gumloop) | 379,557 | -21.1% | Freemium, Paid, Contact for Pricing | Build, share, and control AI agents that actually do the work | [.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 | Specializes in building conversational chatbots and agentic pipelines visually, but lacks broad traditional connector depth. | [.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) |

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

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)