Cheat Layer

Cheat Layer is an AI-powered coding assistant tool designed to solve complex business automation problems. It employs a custom-trained GPT-4 machine learning model, known as Project Atlas, to function as your personal AI software engineer. 

This AI tool streamlines business operations using machine learning combined with no-code platforms. The tool aims to simplify automation by translating it into simple language, making it accessible to users at all levels of understanding. 

Cheat Layer empowers users to automate any browser-based task using its No-Code interface, GPT-3 code creation, action recording, and marketplace features.

Whether you’re a marketer, a self-employed professional, or a small business owner, Cheat Layer can help you automate tasks that were previously too time-consuming or complex to handle.

Cheat Layer Features

Cheat Layer is an automation tool packed with an array of capabilities to enhance your business processes. Some of the key features are:

  • End-to-End Automation: Builds automation like a conversation with an engineer.
  • Growing Library of Cheat Codes: A collection of user-discovered automations.
  • No-Code Drag-Drop Interface: Turn automation into products instantly.
  • Upgrade ChatGPT: Access current events, better than Google.
  • Workflow Automation: Build and run unlimited automations with no-code tools.
  • Webhook Triggers: To extension or cloud.
  • Browser Automation: Specifically for Chrome.
  • Desktop Automation: Coming soon for Mac/Windows/Linux.

Cheat Layer Use Case – Real-World Applications

Cheat Layer is the perfect solution for streamlining business tasks. Its applications include:

  • Data Collection: Automate the scraping of data from various platforms.
  • Marketing Automation: Automate your CRM and marketing workflows.
  • Task Automation: Replace employees or virtual assistants for repetitive tasks.
  • Lead Generation: Automate the collection of leads from platforms like LinkedIn.
  • Content Creation: Use it for automating tasks in Canva.
  • Browser Automation: Automate tasks directly in your Chrome browser.
  • Custom Software Creation: Turn automation into Chrome extensions or desktop apps.

Cheat Layer Pricing

Cheat Layer offers two different plans: workflow automation and enterprise.

The basic plan starts at $49 per month and includes, Craft endless automation with no-code tools. Dive into Project Atlas for new automation, scale with Cheat Cloud, and use webhook triggers. Automate in Chrome, with desktop versions coming soon. Manage unlimited Google Sheets tasks, and upgrade for white-label Chrome extensions. Get live help from Office Hours Consultants.

They also offer an Enterprise plan with custom pricing that includes additional features like custom SLA, rotating residential proxies, and custom team seats. To know more about the pricing details get in touch with the team.

FAQs

What is Project Atlas in the Cheat Layer?

Project Atlas is Cheat Layer’s custom-trained GPT-4 machine learning model that helps in building automation.

Is the Cheat Layer only for Chrome?

No, while Cheat Layer offers automation for Chrome, it also anticipates desktop automation for Mac, Windows, and Linux. Always refer to their latest updates for expanded compatibility.

What kind of tasks can I automate in Cheat Layer?

In Cheat Layer, you can automate web processes in Chrome, manage Google Sheets tasks, and soon, desktop tasks across Mac, Windows, and Linux.

Is there a Cheat Layer free trial?

Yes, Cheat Layer offers a free trial. However, for specifics on duration and features, check their official website or contact support.

How secure is the Cheat Layer?

The Enterprise plan offers features like custom SLA, SSO SAML, and 2FA for enhanced security.

About GilPress

I'm Managing Partner at gPress, a marketing, publishing, research and education consultancy. Also a Senior Contributor forbes.com/sites/gilpress/. Previously, I held senior marketing and research management positions at NORC, DEC and EMC. Most recently, I was Senior Director, Thought Leadership Marketing at EMC, where I launched the Big Data conversation with the “How Much Information?” study (2000 with UC Berkeley) and the Digital Universe study (2007 with IDC). Twitter: @GilPress
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