Crayon Data: What It Is & How It Works
Screenshot of Crayon Data

Crayon Data

Discover what Crayon Data is and how its maya.ai platform helps businesses grow revenue with AI, external data, and machine learning.

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What is Crayon Data?

Crayon Data is a B2B AI solutions company offering an AI-native platform called maya.ai. Its goal is to help businesses grow revenue faster and extract more value from their data, drawing on the company’s expertise in external data and machine learning. Crayon Data has a global presence and an understanding of regional markets, enabling it to build personalized AI solutions tailored to each business. The platform is designed to be flexible, scalable, and secure, making it suitable for businesses of various sizes.

Who created Crayon Data?

Crayon Data was founded by Suresh Shankar, an entrepreneur with a track record in big data, analytics, and digital personalization. He previously founded RedPill Analytics, which was later acquired by IBM. The company has two other co-founders: Aarti Ramakrishnan, who brings experience in marketing and analytics, particularly in the banking, financial services, and insurance (BFSI) sector, and Vijaya Kumar Ivaturi (IVK), an expert in innovation management and advanced technologies.

Who is Crayon Data for?

The platform targets a range of business and technical roles, including:

  • Data Analysts
  • Marketing Managers
  • Business Strategists
  • Sales Managers
  • Product Managers
  • Financial Analysts
  • Customer Experience Managers
  • IT Consultants
  • Operations Managers
  • Project Managers

Key platform components

Crayon Data’s platform is organized into three studios:

  1. Data Studio – The starting point for bringing in, shaping, and refining data.
  2. AI Studio – Where users build AI use cases designed to manage the customer lifecycle.
  3. Analytics Studio – Provides ready-made metrics and visualization tools for building fast analytics and extracting insights.

The studios can be used individually or combined to improve data processing and analysis. Users are encouraged to explore new features, follow best practices, and engage with the Crayon Data community for support, as well as share feedback to help shape the product’s development.

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