
Yutori envisions a future where digital life is liberated from mundane routines, creating "room to breathe" by seamlessly automating everyday tasks through intelligent agents. We exist to reshape the way people and organizations engage with the web, transforming complex digital interactions into effortless experiences that enrich human potential.
Anchored by cutting-edge advances in AI, including foundation models and multi-agent systems, we build autonomous agents that learn, adapt, and act with precision across a dynamic online world. Our work empowers individuals and enterprises with trusted digital collaborators that anticipate needs, drive productivity, and unlock new possibilities for meaningful innovation.
At our core is a commitment to ethical, empathetic design that builds technology as a proactive partner—an AI chief of staff that augments decision-making and craftsmanship, enriching lives by creating space for what truly matters in an increasingly connected, complex future.
Our Review
When we first heard about Yutori, we'll admit we were skeptical. Another AI startup promising to revolutionize productivity? But after digging into what this San Francisco team is building, we found ourselves genuinely intrigued by their approach to personal AI agents.
The company's name comes from the Japanese concept of "room to breathe"—and that philosophy seems to permeate everything they're doing. Instead of building another chatbot, they're creating what they call an "AI chief of staff" that actually gets things done on the web.
Why the Team Caught Our Attention
Yutori's founding story is pretty compelling. Co-founders Devi Parikh, Dhruv Batra, and Abhishek Das aren't your typical startup founders—they're veteran AI researchers who've spent years at Meta's FAIR team, Google's Gemini project, and top universities. What's fascinating is that Parikh and Batra (who happen to be married) had been brainstorming this concept over dinner conversations long before they officially launched the company.
When a team with that kind of pedigree raises $15 million in seed funding from Radical Ventures and Felicis, we pay attention. These aren't investors throwing money at flashy demos—they're betting on deep technical expertise.
What Makes This Different
Here's where Yutori gets interesting: they're not trying to build a better search engine or a smarter chatbot. Their AI agents are designed to autonomously navigate the messy, chaotic web and actually complete tasks—booking reservations, scheduling meetings, coordinating travel, even handling transactions.
We've seen plenty of AI assistants that can answer questions or generate text. But building an agent that can reliably perform multi-step actions across dozens of websites? That's a genuinely hard technical problem, and one that could be incredibly valuable if they nail it.
The Reality Check
Of course, we've heard grand promises about AI agents before. The real test will be whether Yutori can deliver the reliability and accuracy needed for people to actually trust these agents with important tasks. The difference between a demo that works 80% of the time and a product that works 99% of the time is enormous.
But given the team's track record and their focus on "agent-first" technology rather than conversation, we're cautiously optimistic. They seem to understand that the devil is in the details when it comes to building AI that works in the real world.
Who This Could Work For
If Yutori delivers on their vision, we could see this appealing to busy professionals who are drowning in digital tasks, as well as enterprises looking to automate routine processes. The subscription model makes sense, though we're curious to see how they price different service tiers.
Ultimately, Yutori feels like one of the more thoughtful approaches we've seen to the AI agent space. Whether they can execute on that vision remains to be seen, but they've certainly got our attention.
Personal AI assistant (web agent) that autonomously completes complex, multi-step digital tasks
Real-time monitoring, synthesis, and action across multiple websites
Advanced foundation models, reinforcement learning, multi-agent systems, and model-in-the-loop flywheels
Agent-first approach optimized for task completion rather than conversation
Enterprise-grade AI agents for business process automation






