Respond.io Raises $62.5M, Eyes Acquisitions

The Malaysian messaging platform plans to expand into North America and Europe while eyeing strategic acquisitions.

By Central
Respond.io processes 2 billion messages per quarter and has grown to $35 million in ARR.
Highlights
  • Respond.io charges based on conversation volume, not per seat, making it resilient to AI replacing humans.
  • The platform handles 2 billion messages per quarter across channels like WhatsApp, Instagram, and TikTok.
  • CEO Gerardo Salandra plans to take the company public on Nasdaq, despite maintaining disciplined growth.

Respond.io, the Malaysian customer conversation management platform, has secured a $62.5 million Series B funding round led by Camber Partners, with participation from Endeavor Catalyst and existing backers. The investment marks a significant milestone for the Kuala Lumpur-based startup, which has grown to $35 million in annual recurring revenue (ARR) while maintaining a 30% profit margin and an impressive 169% year-over-year growth rate. The company last raised a $7 million Series A in 2022.

From Hong Kong to Kuala Lumpur: The Respond.io Story

Founded in Hong Kong in 2017 by CEO Gerardo Salandra, CTO Hassan Ahmed, and COO Iaroslav Kudritskiy, Respond.io relocated its headquarters to Malaysia two years later. Salandra, whose background includes stints at IBM and Google before joining Runtastic (the fitness tracking app acquired by Adidas in 2015), identified a fundamental shift in how customers want to communicate with businesses. The platform now processes 2 billion messages per quarter, serving mid- to large-sized B2C companies across healthcare, automotive, retail, education, and travel sectors.

How Respond.io’s Platform Works

The software consolidates customer conversations from multiple messaging channels—including WhatsApp, Instagram, TikTok, Messenger, Line, Telegram, WeChat, voice calls, and web chat—into a single interface. It uses AI agents to automatically handle high volumes of customer inquiries, qualify leads, and close sales without human intervention. The company targets what Salandra describes as “high-consideration” businesses, where customers need to speak with someone before making a purchase decision. “You don’t go to a website, put your credit card, and buy a car; you chat with someone, you ask a lot of questions,” he explained. The platform’s sweet spot is organizations with 200 to 10,000 employees.

Why AI Is an Accelerant, Not a Threat

The rise of generative AI tools like ChatGPT has raised an obvious question for platforms like Respond.io: Can these general-purpose AI tools simply replace what specialized conversation management software has built? Salandra argues that the opposite is happening. “If I just look at the numbers, every day that AI becomes more prominent, we grow faster,” he said. “We are not seeing what the public SaaS markets are seeing.”

Part of the resilience comes down to Respond.io’s pricing model. Unlike enterprise software competitors that charge per seat, Respond.io charges based on the volume of customer conversations. This means it doesn’t matter whether a human or an AI is answering the message. “When fewer humans use your product, they make less money,” Salandra noted. “But we don’t charge like that.”

The company also benefits from a structural advantage over incumbent platforms, particularly those dominant in North America and Europe, which were built around email and phone calls. “The platforms that exist, they bolted on messaging as a second thought. They’re very email focused, they’re very call focused, but when it comes to messaging, it’s an afterthought,” Salandra said.

The Data Flywheel Effect

Respond.io’s massive message volume creates a powerful feedback loop. More messages mean better AI training data. Better AI attracts more customers. More customers generate more messages. “This is what we call the data flywheel,” Salandra explained. He emphasized that the company’s head start matters for any upstart AI competitor. “Because we started so long ago and we have such a strong foundation, we can provide better AI compared to someone who just entered into the messaging space.”

Acquisition Strategy and Geographic Expansion

With the new capital, Respond.io plans to pursue hiring, organic growth, and acquisitions. Salandra has two types of buying targets in mind: bolt-on technology that fits into its existing ecosystem, and established teams with strong customer bases in strategic markets like Europe and North America. “Imagine how many months I can save if I find the right company that maybe already has the clients and the team,” he said. “I can save myself six months to a year through an acquisition.” He confirmed the company is already in talks with a couple of potential targets.

The geographic push makes strategic sense. Respond.io currently generates roughly 30% of its revenue from APAC, 30% from Latin America, and 20% from the Middle East and Africa, leaving North America and Western Europe at just 20%. But Salandra says those regions are now its fastest-growing. “They took longer to make the change, but now they’re moving very rapidly into messaging channels,” he said, adding that he expects both regions to become the company’s largest segment within two to three years.

Discipline Over Growth-at-All-Costs

Despite the fresh injection of capital, Salandra is cautious about what comes next. “We don’t want to be a growth at all costs company,” he said. “Even with this money, we’re going to be very disciplined.” But Salandra has bigger plans in mind. “My favorite outcome? Ringing the bell at Nasdaq.”

What This Means for Businesses Evaluating Conversation Management Platforms

For organizations currently evaluating customer conversation management software, Respond.io’s trajectory offers a clear signal: the market is shifting decisively toward messaging-first platforms that are purpose-built for the modern communication landscape. The company’s pricing model, which decouples revenue from human headcount, aligns directly with the AI-driven future of customer service and sales. Businesses should evaluate platforms not just on their current feature set, but on their data advantage and ability to improve AI performance over time. The volume of messages a platform processes today is a strong indicator of how intelligent it will be tomorrow.

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