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Drafter AI

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similarweb
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Monthly visits
Paid
19.5K
#71
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Drafter AI is an all-in-one AI platform that allows businesses to combine various AI technologies into single apps, enabling the effortless creation of AI-powered tools and features without the need for coding expertise

FEATURES

  • 🚀 No-Code AI: Drafter AI allows you to effortlessly craft AI-powered tools and features without writing any code.
  • 🏗️ Build Automation Tools: With Drafter AI, you can build automation tools without hiring a team of ML engineers and waiting for years to get results.
  • 🔌 Connect with 1000+ Tools: Drafter AI allows you to connect with 1000+ tools that you use, making it easy to integrate AI into your existing workflows.
  • 🤝 Ultimate AI Business Partner: Drafter AI is your ultimate AI business partner, providing you with the edge you need to succeed in today’s competitive business landscape.

USE CASES

  • 🚀 AI-Powered Apps: Drafter AI allows users to build AI-powered tools and features without hiring a team of machine learning engineers, saving time and development costs

ADDITIONAL INFO

Release
2020
Location
Latvia
Employees
1 - 10
Tech Used
Bootstrap, Python, Node.js, React, Google Optimize, Django, Express, Wagtail, Express
Platforms
Laptop, Code

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FAQ

Drafter AI is an all-in-one AI platform that combines tens of AI technologies into single apps and executes them automatically. It allows businesses to craft AI-powered tools and features effortlessly, build automation tools without hiring a team of ML engineers, and connect with 1000+ tools they use.
Drafter AI is known for its quick turnaround times, but the exact time it takes to deliver a completed AI solution depends on the complexity of the project. To get started with Drafter AI, businesses need to schedule a discovery call, followed by estimations and roadmap planning, and finally signing a contract.
Drafter AI can assist with a variety of product ideas, including sales intelligence, email processing, media listening, support empowerment, copywriting AI, personalization AI, competitive lookup, and collaboration.
To ensure that the dataset used to train AI models is representative and doesn’t include bias, organizations can prioritize sanitizing datasets, invest in education and workforce development to help people adapt to the new job, and evaluate whether AI’s predictions are fair and unbiased.

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