Real-world data for AI

The training data robots can't get from the internet.

Or voice assistants, or document models, or LLMs. Zangbo collects and labels real-world data, and experts review it before it reaches your model.

LiDAREgocentric videoSpeechDocumentsImagesText
the real world 01 · COLLECT LiDAR speech documents 02 · LABEL 03 · EVALUATE 3D boxes transcripts fields your model
Why now

AI now needs data from the physical world.

10×

Physical AI market growth, from about $5B in 2025 to $50B+ by 2033.1

$6B+

Robotics startup funding in the first half of 2025.2

1. SNS Insider, Physical AI Market Report 2033  ·  2. Crunchbase News, July 2025

How it works

From raw recordings to training-ready data.

01 · COLLECT

Capture what the web doesn't have

  • LiDAR, sensor data and first-person video recorded in real homes and workplaces
  • Speech, documents and images from contributors in the languages you need
02 · LABEL

Annotate to your spec

  • 2D/3D boxes, segmentation, pose and trajectories
  • Transcription, intent and speaker labels
  • Field extraction, classification and text annotation
03 · EVALUATE

Expert review and feedback

  • RLHF and preference ranking by domain experts
  • Factuality, reasoning and safety scoring
  • Results fed back into the next round of collection
Selected work

Recent projects.

SpeechMultilingualPilot

Multilingual transcription pilot

Transcription and quality review across multiple locales for a global customer-experience company.

VideoImageInfrastructure

Web-scale dataset acquisition pipeline

Designed a cloud pipeline to acquire, filter and store large open video and image corpora with tens of millions of clips and images.

See all work