Yellow.ai

Yellow.ai automates support across chat and voice by deploying multilingual AI agents that resolve queries, trigger workflows, and deflect tickets at scale.

Specialization:

Conversational AI, Chatbots, Voice AI Agent, Customer Support Automation, Workflow Automation, Omnichannel Engagement, AI-driven Analytics.

Company Type:

Startup

Total Financing Amount:

$102.2M

Founded Date:

2016

Description

Yellow.ai’s platform uses specialized AI agents to manage customer service across voice, chat, and email. Powered by multiple language models—including its own YellowG (with a sub-1% hallucination rate) and an Orchestrator LLM—it holds context-aware conversations and automates routine tasks. The platform detects sentiment, understands intent, and triggers actions like creating tickets, escalating issues, or sending replies in 135+ languages. It connects easily to tools like Salesforce, Zendesk, and Genesys using 150+ pre-built integrations. Customer service teams use it alongside human agents, with AI handling common requests via VoiceX, chat, and email—while offering real-time suggestions, insights, and customer data in a single dashboard.

Customers

Air Asia, Singapore Airlines, Sony, Hyundai, Philip Morris International

What Problem Does Yellow.ai Solve?

Customer service teams find it challenging to manage large volumes of inquiries across voice, chat, and email without sacrificing response speed or consistency. This creates long wait times, frustrated customers, and overwhelmed agents, ultimately hurting customer satisfaction scores and retention. Yellow.ai's platform automates up to 90% of customer interactions with AI agents that can handle complex requests across all channels, while providing human agents with smart tools and full customer context when escalation is needed.

Pros

• Conversational AI Across Channels: Yellow.ai delivers AI-powered virtual assistants across voice, chat, email, SMS, and social platforms.
• Omnichannel Orchestration: Unified agent design and analytics allow seamless handoff and workflow consistency across all interaction modes.
• Language and Localization Support: Built-in capabilities for multilingual conversations and regional language understanding.

Cons

• Initial Design Overhead: Creating coherent flows across multiple channels and languages requires careful planning and design.
• Customization Demands: Advanced use cases such as transaction-level bots may require developer intervention and SDK use.
• Pricing Model Complexity: Multi-channel deployments and usage tiers may lead to cost unpredictability as volume and features scale.

Last updated: September 9, 2025