Town is building a personal AI assistant designed to behave less like a chatbot and more like a chief of staff. Instead of requiring users to manually feed context through prompts, Town connects across a person's inbox, calendar, Slack, docs, and messages to understand how they actually work, then starts doing the work alongside them, drafting emails, scheduling meetings, tracking projects, handling follow-ups, gathering context, and executing multi-step tasks.
The company's core thesis is that today's AI tools put too much burden on the user. People are expected to become prompt experts, painstakingly supplying context every time they want help. Town inverts this: by learning individual work habits and connecting to the systems where work happens, it proactively offers assistance rather than waiting to be asked. The goal is an assistant that genuinely reduces workload for everyone, not just those willing to master AI tooling.
This ambition places Town squarely in the emerging category of agentic personal assistants, where the differentiator is not a single feature but the ability to operate continuously across a user's tools, maintain context over time, and take initiative on real, multi-step work. Town's product exited beta alongside its funding announcement, launching its Townie assistant to a broader audience.
Town raised a $55 million Series A led by Andreessen Horowitz, with participation from Forerunner Ventures and continued support from First Round Capital, Alt Capital, and Conviction. a16z general partner Alex Rampell joined the board, and the round reflects strong investor belief in proactive, context-aware AI assistants.
For knowledge workers buried in coordination, scheduling, and follow-ups, Town aims to be the always-on agent that learns the job and quietly does it, making AI useful by default instead of demanding expertise from its users.