# Activepieces vs Cheat Layer

Activepieces records 258,553 monthly visits with +1.5% month-over-month growth and Freemium pricing. Cheat Layer records 1,207 monthly visits with -58.6% growth and Free Trial, Paid, Contact for Pricing pricing.

| Metric | [Activepieces](https://openaitools.app/tool/activepieces) | [Cheat Layer](https://openaitools.app/tool/cheat-layer) |
| :--- | :--- | :--- |
| Website URL | https://www.activepieces.com | https://cheatlayer.com |
| Categories | AI Workflow, No-Code&Low-Code, AI Code Assistant, AI Agent | No-Code&Low-Code, AI Agent, Large Language Models (LLMs), AI Marketing |
| Pricing Model | Freemium | Free Trial, Paid, Contact for Pricing |
| Monthly Visits | 258,553 | 1,207 |
| MoM Growth Rate | +1.5% | -58.6% |
| Primary Market | United States | United States |
| Direct Visits | 111,328 | 475 |
| Review Score | 4.6 | 4.1 |
| Saved Count | 0 | 7 |
| 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)

## Cheat Layer

Cheat Layer started as an early startup approved by OpenAI to sell GPT-3 for automation. Its core idea is that language should be the only interface you need: instead of learning a visual builder or writing scripts, you describe the outcome and its agent framework generates the automation end to end. The company describes this as meeting users at their own level of understanding, from simple tasks to multi-step integrations.

The product is organized around three agent categories. Sales agents handle autonomous lead generation and qualification with email, SMS and embedded voice agents, promising higher reply rates through personalization. Marketing agents generate, post and A/B test content across tools such as image and video generators, then iterate based on engagement. Product agents use a live mode to build functional tools, apps, presentations and landing pages the way you would work with a hired engineer, with results hosted and shareable immediately.

Technically, Cheat Layer combines desktop and browser automation on Mac, Windows and Linux with cloud agents, webhook triggers, Google Sheets tasks and an agents API. Plans are billed starting from a $1 entry point, with an unlimited workflow automation cloud tier that includes a set number of cloud agents per day, and an enterprise option that adds custom SLAs, team seats, SSO/SAML and the ability to run Cheat Cloud on-premise for compliance reasons.

**Pricing & Plans:** Entry starts from $1. The main cloud tier bundles unlimited workflow automation and agents, with daily budget controls (for example a $2/day budget) and per-agent execution pricing; additional desktop cloud agent servers are available at a daily rate. Enterprise adds custom pricing with SLA, team seats, SSO/SAML and on-premise deployment. A 60-day money-back guarantee is advertised.

- **Natural-language automations:** Describe the task you want automated and the Project Atlas framework generates an end-to-end workflow, including integrations and multi-step logic.
- **Sales, marketing and product agents:** Purpose-built agent categories for lead generation and outreach, content generation and A/B testing, and building shareable tools and landing pages.
- **Desktop plus cloud execution:** Automations run on Mac, Windows and Linux desktop agents as well as cloud agents, so tasks can touch local software and the browser.
- **Triggers and API access:** Unlimited webhook triggers, Google Sheets tasks and an agents API let you wire Cheat Layer into existing systems.

**Strengths:** Natural-language authoring removes the need to learn a visual automation builder or write code; Covers desktop and browser automation as well as cloud execution, which suits mixed software environments; Dedicated agent types for sales, marketing and product work rather than one generic bot; Advertises a low entry cost with a 60-day money-back guarantee

**Limitations:** Agent-generated automations still require testing, since complex integrations can break when target tools change; Pricing scales with daily agent execution budgets, which can be harder to forecast than flat plans; The marketing claims about dramatic CPM and reply-rate improvements should be validated against your own funnel

[Profile (Markdown)](https://openaitools.app/tool/cheat-layer.md)

## Frequently Asked Questions

### How do Activepieces and Cheat Layer compare in monthly traffic?

Activepieces has 258,553 monthly visits, while Cheat Layer has 1,207. 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%; Cheat Layer has -58.6%.

### 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. Cheat Layer: Free Trial, Paid, Contact for Pricing. Entry starts from $1. The main cloud tier bundles unlimited workflow automation and agents, with daily budget controls (for example a $2/day budget) and per-agent execution pricing; additional desktop cloud agent servers are available at a daily rate. Enterprise adds custom pricing with SLA, team seats, SSO/SAML and on-premise deployment. A 60-day money-back guarantee is advertised.

## 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 | Stronger focus on RAG knowledge bases and LLM application development, but less general business automation. | [.md](https://openaitools.app/tool/dify-ai.md) |
| 6 | [Taskade](https://openaitools.app/tool/taskade) | 539,714 | -9.4% | Freemium | Turn one prompt into live business apps, AI agents and automated workflows | [.md](https://openaitools.app/tool/taskade.md) |
| 7 | [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) |
| 8 | [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) |
| 9 | [Relevance AI](https://openaitools.app/tool/relevance-ai) | 192,083 | -15.5% | Free Trial, Contact for Pricing | No-code AI agents and agent teams for real business workflows | [.md](https://openaitools.app/tool/relevance-ai.md) |
| 10 | [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) |

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Source: https://openaitools.app/compare/activepieces-vs-cheat-layer

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