X (Coming Soon)
Proof of Data
The Global Perception Network for Embodied Intelligence
Digitizing Human Experience to Power the Next Billion Robots. Building the World's Largest DePIN for Ego-centric Data.
Industry Inflection Point
The Next Frontier of AI — From 'Brain in a Vat' to 'Physical Embodiment'
Phase 1: Generative AI — A Red Ocean
  • Fuel: Internet stock data (Text/Image)
  • Bottleneck: Data exhaustion and lack of physical common sense. AI can write a recipe but cannot control a robotic arm.
  • Status: Scaling Law faces diminishing marginal returns in the purely digital world
Phase 2: Embodied AI — A Vast Blue Ocean
  • Trend: General humanoid robot hardware (Tesla Optimus, Figure 01) is ready, but the "brain" remains blank
  • Pain Point: "Moravec's Paradox" — sensorimotor skills easy for humans are extremely difficult for robots
  • Core Gap: Lack of first-person (ego-centric) behavioral data
"The next wave of AI is physical AI." — Jensen Huang, CEO, NVIDIA
"The next north star for AI is Spatial Intelligence." — Fei-Fei Li, Godmother of AI
The Data Bottleneck
Embodied AI Is in a "Data Desert" — Like the Era Before GPT-1
The internet is a "text goldmine" but an "action wasteland."
The enormous data gap is the lock that blocks robots from achieving general intelligence.
"The Internet is very text-rich, but it is action-poor." — Andrej Karpathy, OpenAI Co-founder, Former Tesla AI Director
"The limiting factor is data. It's getting the data of humans doing the tasks." — Elon Musk, CEO, Tesla
Solution
PoD — The "Data Eye" and "Tactile Nerve" for Embodied Intelligence
Core Strategy: Human-as-a-Sensor — Since simulators cannot perfectly replicate the laws of physics, we use real humans to 'rehearse' life on behalf of robots.
Hardware Layer
A matrix of wearable devices (glasses frames/clips, gloves) collecting RGB video, depth information, IMU inertial data, and more — at low cost
Software & Protocol Layer
A Web3-based Proof of Data protocol enabling data ownership verification, privacy desensitization, and value transfer
Delivery Layer
Providing robot manufacturers with Sim-to-Real 4D training datasets
"Tesla hires employees in factories to collect data (expensive, limited scope); PoD mobilizes hundreds of millions of people globally to collect data in the real world (affordable, highly diverse)"
Core Product
Low-Cost, High-Precision "Data Mining Rigs"
DePIN Data Collection Hardware Matrix
PoD Smart Glasses Frame / Clip Camera
Function: Captures first-person (ego-centric) video; compatible with both non-prescription users (frames) and prescription users (clip-on)
Use Cases: Records how humans observe the world and navigate complex environments (e.g., kitchen cooking, outdoor exploration)
PoD Half-Finger Data Glove
Function: Captures fine hand movements, acceleration, and more
Value: Captures "force feedback" and "micro-operations" that video cannot record — the key to teaching robots dexterous hand skills
$100
Consumer-Grade Pricing
Sold as a "production tool" — a mining-rig-style ROI model
6-DoF
Fine Hand Motion Capture
EMG electromyography signal + full acceleration capture
4D
Training Datasets
Sim-to-Real high-quality delivery
GTM Strategy
Three-Phase Strategy — Leveraging Software Networks to Unlock the Hardware Ecosystem
A "Trojan Horse" approach — from software to hardware
01
Phase 1: Live Now
Entry Point: Web platform (data task gig platform) + Twitter plugin (voice collection) + Mobile app (video data, etc.)
02
Phase 2: 2026 H2
Conversion: Sell / airdrop PoD hardware to high-reputation users filtered from Phase 1
Scenario: Launch premium "embodied data tasks"
03
Phase 3: 2027+
Scale: Build a network of millions of active hardware nodes.
Action: Launch an embodied intelligence dataset marketplace. Establish joint labs with robot manufacturers
Moat: Become the world's largest owner of unstructured physical behavioral data
Supplementary Data Network
Beyond Motion — Comprehensive Multi-Modal Data Supply
In addition to embodied AI data, PoD's software side generates cash flow businesses:
Voice Data
Addressing the shortage of multilingual, dialect, and emotional data for large language models
Medical Data
Based on "data portability rights," users voluntarily upload medical records and imaging, bypassing hospital B2B barriers to serve medical AI
Competitive Intelligence Data
Users authorize access to Amazon/TikTok browsing records, building a "god's-eye view" commercial intelligence network

The cash flow generated by these businesses will fund hardware R&D while enriching AI's understanding of human society (Context)
Competitive Advantage
Low-Cost, Large-Scale Robot Data Collection Model
Technical Moat
Academically-Led New Paradigm of "Human-Machine Collaboration"
MegaPairs (Production Efficiency)
LLMs synthesize 90% of baseline data; humans only collect the 10% long-tail high-difficulty data, improving efficiency by 100x
BoostER (Quality Verification)
Verification algorithm based on "uncertainty entropy." LLMs review first; questionable data is distributed to high-reputation nodes for "adversarial verification." Cost reduced by 90%
QualBench Standard
Establishes automated evaluation benchmarks for vertical industries, ensuring high-quality data delivery out of the box
DePIN Protocol
Hardware anti-counterfeiting technology based on TEE (Trusted Execution Environment) and MPC (Multi-Party Computation), ensuring data sources are authentic and tamper-proof
Tokenomics
A Decentralized Asset with "Positive Externalities" for the AI Era ($POD)
Data Asset Ownership & Provenance
Only Web3 can give users or Agents true "ownership" and "revenue rights" over their data
Cross-Border Micro-Payments
Enables users in Africa, Southeast Asia, and Latin America to instantly receive $0.1 in task rewards (impossible with fiat currency)
Global Consensus
BTC is the consensus of computing power; ETH is the consensus of applications; $POD is the consensus of "human experiential data"
Large-Scale, Low-Cost User Acquisition
Web3 is the best method for acquiring users at scale and low cost. Data production will replace food delivery and ride-hailing as the largest gig economy model
Integrating Agents into the Network
The network and payment infrastructure compatible with the Agent and Web4 era must be built on Web3. Supports Agents hiring humans to collect data

💡 Positive Externality Flywheel: Faster robot development → Greater demand for data → More active PoD hardware nodes → $POD buyback and burn increases → Token value rises
Deflationary Model: Future B2B enterprises purchasing data must consume $POD
In an age where AI is taking over computation,
PoD defends the value of human perception.
Join PoD, Power the Embodied Future.
Contact
Get in Touch
Email
contact@proofofdata.ai