Ando wants to take on Slack with a team messaging app that lets humans and agents work together

Your messaging app now offers AI agents their own identities, allowing them to participate directly in conversations, potentially reducing your role as an intermediary.

Ando, a new startup, has launched a team messaging application designed to integrate both human and AI agents into daily workflows. Founded by Sara Du, the platform aims to address limitations in existing communication tools like Slack and Microsoft Teams, which Du believes were not built with AI agents as active participants in mind. Ando provides AI agents with their own identities and inboxes, allowing them to join conversations, understand context, ask questions, and collaborate with humans and other agents naturally. The platform supports channels, direct messages, group chats, and live calls, enabling agents to proactively engage in discussions and notify humans when necessary. This approach seeks to eliminate the need for "meat proxies," where humans act as intermediaries for AI agent tasks. The company emerged from stealth with $20 million in pre-seed and seed funding from investors including Accel, Index Ventures, and Emergence, to further develop its AI-agent-native communication solution.

Ando's approach signifies a potential paradigm shift in workplace collaboration, moving beyond AI as mere tools or bots to AI as integrated team members. This could redefine productivity by offloading coordination, research, and execution tasks to agents, freeing humans for strategic and judgment-based work. The success of Ando may pressure incumbent platforms to accelerate their own integrations or risk becoming outdated.

The $20 million funding round signals strong investor confidence in the AI-native communication market, despite competition from established players like Slack and Microsoft. Ando's ability to attract users to its "jankier" initial interface suggests that the core value proposition of seamless human-agent collaboration is a significant unmet need. Future developments will focus on how effectively agents can manage complex tasks and scale small teams.