Poke, an AI agent that lets users automate tasks via text message, raised $10M, on top of a $15M seed in 2025, at a $300M post-money valuation
Is Poke an OpenClaw for the rest of us? That's the idea coming from a new startup offering an AI agent that you can access via iMessage, SMS, Telegram, and, in some markets, WhatsApp.
Context & Ripple Effects
Poke is positioning the messaging inbox—not a standalone app—as the surface for using an AI agent across SMS, iMessage, Telegram, and WhatsApp. Its funding round assigns a substantial valuation to that distribution thesis before the product’s reach across those channels is fully proven.
The subsequent approval for Apple’s Messages for Business platform shows why channel access is central to Poke’s arc: agent capability alone is not enough if the service cannot operate within the messaging environments where users already work and communicate.
First-order effects
- The new capital gives Poke resources to develop and operate its text-accessible agent while its $300M post-money valuation sets a high investor benchmark for execution.
- Poke’s messaging-first approach offers users an alternative to opening a dedicated AI interface for task automation, across the channels it supports.
Second-order effects
- Competing agent builders face added pressure to make their products reachable in existing communication surfaces rather than relying solely on proprietary chat apps; reported work on Meta’s OpenClaw-like assistant points to the same distribution contest.
- Messaging platforms become more consequential gatekeepers: integrations and approvals can determine whether an agent can turn a conversational interface into a usable workflow channel.
Third-order effects
- If messaging-native agents gain sustained use, the agentic-work-surface market could shift from standalone assistants toward embedded services that compete on channel access, reliability, and task completion rather than model access alone.
- This model also concentrates leverage with platform operators that control messaging APIs and business channels, making partnership and policy access a structural constraint for agent startups.
The trend: This is one data point in the shift toward embedded AI agents that meet users inside existing communication workflows rather than requiring a separate destination app.