Malaysia’s AI agent-powered messaging app Respond.io raises $62.5M, eyes acquisitions

2026-06-16 · Source: AI News & Artificial Intelligence | TechCrunch · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, E-commerce & Digital Commerce · Depth: Novice, short

Summary

Malaysia-based customer conversation management software provider Respond.io has secured a \$62.5 million Series B funding round, led by Camber Partners, with participation from Endeavor Catalyst and existing investors. Founded in 2017, the company previously raised a \$7 million Series A in 2022 and has achieved \$35 million in annual recurring revenue (ARR), demonstrating 169% year-over-year growth and a 30% profit margin. Respond.io's platform helps mid- to large-sized B2C businesses manage customer interactions across various messaging channels, including WhatsApp and Instagram, utilizing AI agents to automate inquiries, qualify leads, and close sales. The company processes 2 billion messages per quarter and differentiates itself with a volume-based pricing model, contrasting with per-seat enterprise software. With the new capital, Respond.io plans strategic hiring, organic growth, and acquisitions, targeting bolt-on technology and established teams in key markets, particularly North America and Western Europe, which currently account for 20% of revenue but are rapidly growing.

Key takeaway

For AI Product Managers evaluating customer engagement platforms, Respond.io's success highlights the strategic advantage of a messaging-first approach combined with AI agents. Your focus should be on solutions that offer volume-based pricing, which better accommodates AI-driven automation, rather than traditional per-seat models. Consider how a "data flywheel" can enhance your AI's performance and prioritize platforms built natively for messaging to avoid the limitations of email/call-centric incumbents.

Key insights

Respond.io leverages AI agents and a data flywheel to scale B2C messaging, differentiating from legacy platforms.

Principles

• Volume-based pricing aligns with AI automation.
• Messaging-first platforms outperform bolted-on solutions.
• Data volume creates a powerful AI feedback loop.

Method

The platform automates customer conversations across multiple messaging apps using AI agents for inquiry handling, lead qualification, and sales closure.

In practice

• Implement AI agents for high-volume customer inquiries.
• Prioritize messaging channels for B2C sales.
• Consider volume-based pricing for AI-driven services.

Topics

• Customer Conversation Management
• AI Agents
• Messaging Platforms
• Series B Funding
• B2C Sales Automation
• Data Flywheel

Best for: Product Manager, Entrepreneur, Director of AI/ML, AI Product Manager, Investor

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI News & Artificial Intelligence | TechCrunch.