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Yellow.ai

Customer service automation.
General Information
Founders:
Jaya Kishore Reddy Gollareddy, Raghu Ravinutala, Rashid Khan
Founded Date:
2016-01-22
Total Funding Amount:
$102,150,000
Headquarters Region:
San Francisco Bay Area, Silicon Valley, West Coast
Domain Rating:
71
Organic Traffic:
22480
Last Equity Funding Amount:
$78,150,000
Last Equity Funding Date:
2021-08-04
Last Equity Funding Type:
Series C

Overview

Yellow.ai is an AI-powered platform that helps businesses automate customer support, sales, and engagement through conversational AI solutions. Its intelligent virtual assistants are designed to provide human-like interactions across multiple channels, improving efficiency and enhancing customer experiences. Yellow.ai’s platform supports industries of all sizes, offering seamless integration with existing systems and tools for scalability and customization.

Key Features

  1. Conversational AI: Delivers intelligent virtual assistants capable of handling customer inquiries and automating workflows with natural, human-like interactions.
  2. Omnichannel Support: Operates across channels like chat, email, voice, and social media to ensure consistent and connected customer experiences.
  3. AI-Driven Analytics: Provides actionable insights and recommendations based on user interactions to enhance decision-making and service optimization.
  4. Customizable Solutions: Offers flexible options for tailoring bots to specific business needs, ensuring relevance and efficiency.
  5. Seamless Integrations: Connects with existing CRM, ERP, and other enterprise tools to streamline operations and improve workflows.
  6. Automation Tools: Automates repetitive tasks such as ticketing, FAQs, and lead generation, enabling teams to focus on higher-value activities.

Pros

  • Automates customer interactions for increased efficiency.
  • Supports omnichannel engagement for consistent experiences.
  • Provides valuable insights with AI-driven analytics.
  • Customizable for various industries and use cases.
  • Integrates easily with existing enterprise tools.

Cons

  • Complex use cases may require advanced configuration.
  • Costs may be higher for small businesses with limited budgets.
  • Dependence on accurate data for optimal AI performance.
  • Initial setup can be time-intensive for large-scale deployments.

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