Detect change · Predict outcomes · Guide action

Shared, persistent site record for people and robots

We join what site capture shows with what the ledgers and drawings say, so what is where and what has changed stays in one place, for site teams now and robots next.

One 16-minute walk with a 360° camera · 2026-09-10

Featured in
WIREDNikkei
Backed by
Abelia CapitalIncubate Fund
Recognized by
Institute of Science TokyoOIST InnovationMIT Association of Japan Venture ForumNEDOStartup Initial Program OSAKA (SIO)

YODO LABS Inc.Formerly PixelX Inc.

Product
YODO Asset World

Film the unit in front of you. Its record opens.

YODO Asset World works out where the camera is standing from the image itself, so the unit in frame resolves to one ledger row even among identical machines. What the site already knows about that one unit opens on the spot, with nothing fixed to the asset and nothing to scan.

  1. 01

    Point the camera

  2. 02

    Locate

  3. 03

    Read

Customers

Machines, trees, bicycles: each one in frame is tied to its own row in the ledger.

From mines to city streets, we have worked alongside six kinds of site. At the airport and in the factory, robots have started to use the record too.

RICOH
Machine rooms and plants

From 360° video, each machine is matched to its row in the equipment register.

Ricoh (technology partnership)Full write-up coming soon

サキュレ
Roads and streets

From patrol video, everything on the street goes into the register, one by one.

SakyureFull write-up coming soon

GHD
Mining

Equipment identified from video, so decisions at the mine are faster and surer.

GHDFull write-up coming soon

NEDOMETI
Airport

A baggage-handling robot recognises each bag and what surrounds it.

NEDO · METIFull write-up coming soon

Three robotics companies
Factory

Robots from three companies work from the same record.

Full write-up coming soon

Technology

What people read today, robots will act on next.

A robot senses that something is there. What it is, and what has happened to it, sits in the record, and it is the same record people on site already read.

What one camera, person or robot has seen reaches all the others, so a robot can pick up where a person left off.

A robot's point of view. The frame goes to YODO Asset World and comes back with the unit's record.

The record rests on four technologies, set out below.

01Localization

Ledger-bound reconstruction

A single handheld pass returns the site in real units, every object bound to a ledger row by where it stands. A planner can collide against it, a work order can cite it.

02Detection

Scene chronology

The second visit is the hard part: the same unit, a different device, distance and angle. Recognise it and captures accrue into a record, every earlier state still recoverable.

03Forecasting

Asset intelligence

Condition forecasts come off the rounds a site already walks, with nothing instrumented. The forecast stays inside what the rounds have observed, and what comes back is a dated work item.

04Grounding

Native 3D answers

Spatial questions are usually answered from flat frames, with the depth inferred afterwards. This model works natively in 3D: it outlines the region it is about to measure inside the point cloud, then reads the number off that geometry, so number and evidence arrive together.

Team

Xiuxi Pan, PhD

Xiuxi Pan, PhD

Cofounder & CTO

Published work in Computer Vision, Computational Imaging, Generative Model. Led the production and implementation of AI solutions for major Japanese and international enterprises. Profiled by WIRED and Nikkei as an early pioneer of AI in Japan.

Sho Osawa

Sho Osawa

Cofounder & CEO

Former strategy consultant at Strategy& (PwC) and Westpac Banking Group. Scaled a SEA start-up insurer from zero to 150M in insured exposure in two years, leveraging automation and AI.

Bona Bai, PhD

Bona Bai, PhD

Robotics Lead

15 years building autonomous systems across Amazon (Astro), Google Wing, and Figure AI. Full-stack autonomy from sensor fusion and perception through to real-time decision making.

Prof. Tomoya Nakamura

Prof. Tomoya Nakamura

Research Advisor

Professor at The University of Osaka and Visiting Professor at Stanford University. Computational Imaging, Computer Vision, AI Optics.

Build with us

We work with robotics teams and industry partners who are putting people and robots into the same changing spaces.

Running a site

Start with one inspection video. See what YODO Asset World finds.

Building robots

Give your robot what the rest of the site has already seen.

Joining the team

We are hiring, starting with a founding business member. If no listed role fits, write to us anyway.