AI Startup Aims to Streamline Your Calendar Negotiations

Kais Khimji has built his career as a venture investor, with six years as a partner at the renowned VC firm Sequoia Capital.

However, like other former Sequoia partners—such as David Vélez, founder of Brazilian digital bank Nubank—Khimji (pictured left) always aspired to launch his own startup. This Thursday, he announced the revival of an idea he first developed as a Harvard student nearly a decade ago, now realized as the AI scheduling company Blockit. In a strong endorsement, his former employer Sequoia led the company's $5 million seed funding round.

"Blockit has the potential to grow into a billion-dollar revenue business, and Kais will ensure it reaches that goal," wrote Pat Grady, Sequoia's general partner and co-steward who led the investment, in a blog post.

While numerous startups have attempted to automate scheduling, Khimji believes recent advances in large language models (LLMs) enable Blockit's AI agents to manage the process more seamlessly and efficiently than earlier solutions, including now-defunct companies like Clara Labs and x.ai. (That domain name is now owned by Elon Musk's AI venture.)

Unlike category leader Calendly—valued at $3 billion and reliant on users sharing links to compare availability—Blockit bets its AI agents can master the nuanced, entire scheduling workflow without human input.

With Blockit, Khimji and co-founder John Hahn—who previously worked on calendar products including Timeful, Google Calendar, and Clockwise—are building what amounts to an AI-powered social network for managing time.

"It always seemed strange. I have a time database—my calendar. You have a time database—your calendar. Yet our databases simply can't communicate," Khimji told TechCrunch.

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Khimji states that Blockit finally resolves this disconnect. When two users need to schedule a meeting, their AI agents communicate directly to negotiate a time, completely eliminating the usual email chain.

Users can activate the Blockit agent by copying it on an email or messaging it in Slack about a proposed meeting. The bot then handles the logistics, finding a mutually convenient time and location that aligns with all participants' preferences.

According to Khimji, Blockit operates as smoothly as a human executive assistant. Users simply provide the system with specific instructions about their preferences, such as which meetings are fixed and which can be rescheduled based on daily demands. "Sometimes my schedule is packed, so I might need to skip lunch. The agent needs to understand that's acceptable," he explained.

The system can even be trained to prioritize meetings based on email tone. For example, a user could instruct the agent that a request signed formally with "Best regards" should take priority over a casual note ending with "Cheers."

By learning user preferences, Blockit seems to leverage what Foundation Capital partners Jaya Gupta and Ashu Garg term "context graphs." In a widely circulated essay, the investors describe a multibillion-dollar opportunity for AI agents to capture the underlying rationale behind business decisions—the hidden logic that previously existed only in a person's mind.

Blockit is already used by over 200 companies, including AI startup Together.ai, recently acquired fintech Brex, robotics startup Rogo, and venture firms a16z, Accel, and Index. The app offers a free 30-day trial. After that, individual plans cost $1,000 annually, while team licenses supporting multiple users are $5,000 per year, Khimji said.