Surface local tech networking events and register for them entirely via text messaging

What is text-driven event discovery and registration automation?

Text-driven event discovery and registration automation is the autonomous workflow where an AI agent receives natural language instructions via mobile messaging channels (iMessage, SMS, or Telegram), searches event aggregators for relevant local gatherings, clarifies edge cases directly with the user over chat, and navigates registration pages to complete ticket sign-up forms on the user's behalf.

For founders, engineers, and operators in tech hubs like San Francisco, New York, or London, high-signal networking occurs primarily at offline meetups, hackathons, and demo nights hosted across platforms like Luma (lu.ma) and Eventbrite. However, discovering these sessions requires manual monitoring of community boards, and registering demands repetitive form-filling for each individual ticket. Autonomous text-driven delegation bridges the physical-digital divide: users delegate the objective via a single conversational message, the agent filters and registers across external portals, and calendar entries populate the user's schedule automatically.

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Method comparison: Approaches to tech event discovery and RSVPing

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How Sai handles mobile commands, interactive edge cases, and registration forms

The challenge of conversational autonomy

Autonomous agents often fail in open-ended real-world tasks because real queries contain hidden ambiguities. For example, a search for "SF tech events" may return:

• Events located in distant cities that mention San Francisco companies in their description (e.g., a London networking session hosted by a Bay Area venture firm).
• Paid ticket tiers requiring credit card approvals.
• Events requiring customized survey questions (e.g., "What is your GitHub handle?" or "Dietary restrictions?").

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The proactive secretary interaction model

Sai solves this through a human-in-the-loop mobile architecture:

1. Conversational trigger via SMS / iMessage: The user texts Sai naturally while on the go: "Find offline tech events in SF this week and register for them".
2. Multi-portal aggregation & location filtering: Sai connects to the web browser, traverses Luma (lu.ma) and Eventbrite, extracts event dates, venue addresses, and ticket statuses.
3. Mid-task interactive clarification: When encountering an ambiguous result—such as an event tagged under a Bay Area community but physically taking place in London—Sai does not guess or abort. It sends a brief text back to the user: "Found 3 events in SF. Also found a London session from the same host—should I skip London?".
4. Resumed autonomous execution: Upon receiving the user's short reply ("Skip London, register the rest"), Sai proceeds to the registration modal for each SF event, enters the user's verified contact details, submits the ticket orders, and confirms that official calendar invites land in the user's inbox.

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Output schema: The event registration record