Ando Emerges from Stealth with $20M to Redefine Workplace Collaboration for AI Agents

When Sara Du began assisting companies with the development of Model Context Protocol (MCP) servers in 2025, she noticed a recurring pattern in the feedback she received. Clients were increasingly eager to integrate AI agents directly into their existing messaging workflows within platforms like Slack. However, the path to seamless integration was blocked by significant technical hurdles. Organizations struggled with the friction of moving data back and forth between silos and, more importantly, ensuring that agents had access to the right context without triggering prohibitive token consumption costs.

As Du delved deeper into these technical challenges, she realized that the issue was not merely one of API limits or software integration; it was a fundamental architectural flaw in how modern communication platforms were conceptualized.

“The deeper I went, the more I felt Slack and Teams were built for a world that was starting to pass us by,” Du told TechCrunch. “Agents were treated as apps you install even as they were becoming participants in the team.”

This observation led to the founding of Ando, a startup that officially emerged from stealth on Thursday with a $20 million infusion of pre-seed and seed funding. Backed by prominent venture capital firms including Accel, Index Ventures, and Emergence, the company aims to provide a comprehensive replacement for traditional messaging platforms. Unlike existing tools that bolt AI onto a human-centric interface, Ando is designed from the ground up as a native environment for both human and AI workers.

The Problem of the "Meat Proxy"

At the heart of Du’s critique is what she describes as the "meat proxy" phenomenon. In current professional settings, AI agents often perform significant analytical or creative work, but they lack the agency to share that work directly with the team. Instead, a human employee must act as an intermediary, relaying the agent’s findings, translating its output into a readable format, and manually coordinating the next steps.

“The human effectively becomes the messenger between the agent and the rest of the company,” Du explained. She argues that this model is inefficient and fundamentally misunderstands the potential of artificial intelligence in a professional setting.

An ideal system, according to Du, would not treat AI as a secondary utility but as a peer. Her vision for Ando is a workspace where agents can participate in the shared conversations where work is actually coordinated. Ideally, these agents should be able to understand the historical context behind a specific business decision, proactively query a colleague for clarification, build upon the outputs of other agents, and identify the precise moment when human judgment is required to move a project forward.

Designing a Native Environment for AI Agents

Ando functions as a full-featured team messaging platform, complete with channels, direct messages, group conversations, and voice capabilities. However, its differentiating factor is its treatment of artificial intelligence. In the Ando ecosystem, agents are granted their own identities and dedicated inboxes. They are not merely passive responders triggered by commands; they are active participants that can navigate the platform with a degree of autonomy.

Agents in Ando have the capability to browse channels, choose which conversations to join based on their utility, and engage in threads without needing to be explicitly tagged by a human. If an agent determines that a particular development requires human intervention, it is empowered to message that worker directly, removing the need for internal approval bottlenecks or administrative oversight that slows down decision-making.

The platform even supports live calls, which are transcribed in real-time, allowing agents to ingest the conversation and provide immediate assistance or follow-up actions. By embedding agents into the core flow of information, Ando aims to bridge the gap between AI capability and organizational execution.

Navigating a Crowded Competitive Landscape

Ando is entering a market that is already being aggressively contested by the world’s largest software companies. The "collaboration space" has become a central theater for the AI arms race. Slack has evolved its native bot into a more capable AI agent, while Microsoft has invested heavily in integrating its Copilot assistant throughout the entire Office 365 suite and Teams, aiming to make AI an inescapable part of the daily workflow.

Despite the dominance of these incumbents, Du remains convinced that there is a significant market opportunity for a purpose-built platform. She argues that legacy platforms, despite their massive user bases, are essentially trying to retrofit AI into software architectures that were designed for a purely human workforce. This creates a "pivot" challenge that she believes leaves room for agile, agent-native challengers.

Recent industry movements support the idea that the market is still in flux. Just a few months ago, Twitter and Block co-founder Jack Dorsey introduced Buzz, a group chat platform specifically designed to bring people and AI agents together. While Buzz appears to be more focused on developer-centric use cases, its emergence underscores a broader industry consensus: the way we communicate at work is undergoing a seismic shift.

The Learning Curve of Innovation

Developing a new category of workplace software is not without its risks. Du openly admits that the early days of Ando were difficult, noting that initial feedback was often lukewarm. Potential users, accustomed to the feature-rich environments of established tools, were initially unimpressed by what they perceived as a stripped-back or "jankier" messaging platform.

“A lot of people we showed it to early on were understandably unimpressed. It was, in many respects, just a jankier messaging platform. People would get stuck on that before they even got to what was different about the agents,” Du said.

The turning point for the team came when they shifted the focus toward demonstrating the long-term utility of autonomous agents. As users spent more time in the platform, the benefits of having an agent-native environment became apparent. Du recalls instances where an agent, operating autonomously, noticed that two separate channels were discussing the same technical challenge. Without waiting for a human to connect the dots, the agent brought the relevant participants into a single group chat, summarized the shared context, and proposed a path forward.

For Du, this was a moment of validation. “That was really delightful for me,” she said. “I felt agents could better manage people than humans can because they can process a lot more messages than a human can in a shorter span of time.”

Scaling the Agent-First Future

Currently, Ando is working with a diverse range of customers across sectors including software, real estate, and finance, with a presence spanning 15 countries. While many of the initial teams are small, Du believes the platform will eventually enable teams of all sizes to operate with a degree of efficiency that was previously impossible.

The fresh $20 million in capital will be directed toward scaling the team and, as Du candidly noted, "burning through more tokens." As the company expands, the focus will remain on the core philosophy that AI is not just a tool, but a teammate.

“I think agents will let very small teams operate at a scale that previously required hundreds of people,” Du said. “They can take on more of the execution, research, and coordination work, while humans spend more of their time on judgment, strategy, and deciding what should happen next.”

As Ando continues to refine its interface and agent capabilities, the industry will be watching to see if a native-first approach can indeed displace the giants of workplace communication. For now, the startup is betting that the future of work is not just about using AI, but about working alongside it in a space designed to accommodate the speed and scale of artificial intelligence.