[MeeeetUp Inc.] The \"Offline Cookie\": Unlocking Real-World Customer Behavior via Encrypted Face-Recognition IDs

Replicating Online Cookie Analytics in Physical Spaces

Hello, everyone. My name is Kazuya Takahashi, Representative Director of MeeeetUp Inc. It is a pleasure to be here today.

MeeeetUp is an innovative startup providing the \"Offline Cookie\" or \"Real-World Cookie\" platform. We utilize face-recognition technology to help business operators analyze and understand customer behavior in physical spaces.

In the digital realm, tech giants like Google and Meta have used browser cookies to track which pages users visit, what they look at, and what they buy. However, in the physical (offline) world, there has been no high-precision method to capture similar customer journey data. MeeeetUp bridges this gap between online and offline customer analytics by utilizing face-recognition and proprietary encrypted ID technology.

Traditionally, capturing offline customer data faced major hurdles:

1. The Active-Action Barrier: Collecting data has been difficult because it requires users to scan QR codes, download apps, or fill out forms. Incentives used to bypass this barrier often introduce demographic bias.

2. The Merging/De-duplication Challenge: Even when data is collected across different properties, minor typos in email addresses or names make it difficult to link the data to a single individual. This splits customer profiles within CRM systems, preventing a unified customer view.

3. Analysis Time Lag: Verification and matching processes require manual entry, making it impossible to analyze and utilize gathered data on the spot.

MeeeetUp solves all of these challenges by utilizing the human face as the primary identifier.

Plug-and-Play Setup: Using Existing iPads to Log Journeys Without User Friction

Our platform collects face data, de-duplicates entries, and aggregates all customer journey logs under a unique, secure \"Face ID.\"

Deployment is simple: operators place any camera-equipped device—such as an existing iPad or iPhone—at event receptions, coworking spaces, or retail booths. Users do not need to download apps or show membership cards. By simply standing in front of the camera, their check-in is logged automatically.

Once captured, the face data is linked to a unique, recurring Face ID. This enables operators to detect returning customers across different days and track their journeys across separate floors or properties, delivering instant dashboard analysis.

MeeeetUp connects easily to existing reservation and customer management databases via API, ensuring deployment without putting operational strain on frontline staff.

Although we launched only four months ago, our platform is already used by approximately 40 enterprises and local governments, securing over 5,000 registered users. We support B2B business matchmaking receptions, coworking check-ins, campus tours (digital stamp rallies), and even evacuation registrations for local governments.

Encrypted Face Hashes: A Unified \"Register Once, Use Anywhere\" Identity Network

Our primary competitive moat lies in our proprietary encrypted face-hashing technology and our pure SaaS model.

Most existing face-recognition solutions are bundled with expensive proprietary hardware and operate on isolated databases. Users must register their faces separately at every gym, office, or apartment building they visit, creating a tedious user experience.

We address this by converting face images into irreversible, encrypted hash IDs, eliminating the risk of personal data leaks. As a result, once a user registers their face on the MeeeetUp network, they can check in at any participating property or event without registering again.

Our business model does not require hardware purchases. Basic deployment is free. We charge a monthly subscription fee of 100 to 500 JPY per active ID for advanced analytics, customer management, and dashboard reporting.

While we initially target reception cost reduction for event organizers, our long-term value lies in our data platform. We visualize offline interests—such as which booth a visitor spent time at—to help organizers maximize sponsor value and revenue.

Our goal is to reach 12 million active users in Japan (approx. 10% of the population) by 2030, securing 12 billion JPY in ARR based on a projected annual value of 1,000 JPY per ID. We are raising seed capital to accelerate our development. We look forward to connecting with investors and strategic partners. Thank you.

Q&A and Feedback

Mr. Ito (Commentator): Thank you, Takahashi-san. Building an offline customer database by safely hashing face IDs without violating privacy has significant marketing potential.

How do you plan to scale this from event receptions into a broader business model?

Mr. Takahashi: We are using small-to-mid-sized event receptions as our entry point, but our ultimate goal is to build a municipal人流 (human flow) data platform.

We plan to link visitor interest data captured at events with retail malls, theme parks, and transit networks. By linking offline journeys across time and space, we can visualize area-wide consumer patterns, driving retail referrals and maximizing sponsor fees.

Mr. Ito: Understood. So it is a human-flow data platform rather than basic check-in software.

Since face-recognition engines from AWS and Google have become commodity tools, what is MeeeetUp's core technical moat?

Mr. Takahashi: It is true that matching engine technology has normalized. Our core advantage lies in our database structure and privacy governance.

Competitors build isolated databases for security purposes (like gym entries), preventing data sharing. We designed MeeeetUp as a unified marketing ID network. We convert face data into irreversible hashes and share them across different businesses under a secure, opt-in privacy framework. This unified ID network effect is our primary competitive moat.

Mr. Ito: The fact that it requires no hardware and runs on a standard iPad is a compelling selling point for events. I wish you the best for this seed round.

Mr. Takahashi: Thank you. We will work to become the standard for offline identity networks.