The World's First Supply-demand Balanced
and Always-online AI Inference Network

Global users can now earn rewards by sharing idle computing resources or by
asking questions through Depai's Llama and Gemma AI inference services,
promoting resource sharing and technological advancement.

Functions

Decentralized AI Cluster

Integrate global computing resources to
build an AI cluster based on DePIN.

Deliver Ubiquitous AI Inference
Services to Users

All types of devices, including smartphones, laptops, and
personal computers, can easily access and use efficient AI
a model inference services.

Provide AI Development Support
for Developers

Offer OpenAI-compatible APIs to supply developers with
online AI inference services like Llama and Gemma,
accelerating the development process.

Provide Cost-effective AI Computing
Resources for Enterprises

Through Depai, enterprises can obtain AI
computing resources with higher cost-
effectiveness than traditional cloud computing
service providers.

Core Technologies

Features

Always Online

Complete decentralization ensures that
Depai is always online.

Ultra-Fast Response

The nearest and best-matched worker is
scheduled to complete AI inference tasks,
obtaining extremely fast response speeds
through streaming interfaces.

Innovative PoW

Workers prove their work through AI
tasks and are rewarded according to the
work they complete.

Earn More

Workers can earn rewards for completing AI inference tasks or for
being effectively online; users can also earn rewards for using AI
services.

Dynamic Supply and Demand Balance

Through Depai's API, developers can create a diverse range of
AI applications, achieving a balanced network of supply and
demand, and continuously optimizing the user experience.

Network Metrics

1.58K

Total Q&As for User

4.82K

Total AI Inferences by
Worker

1

Online Workers

5.38M

Total U Points Earned
by Users

1.09B

Total W Points Earned
by Workers

Roadmap

Phase 1: Testnet Development

Website development

Whitepaper creation

Validator development

Worker client development

Worker dashboard development

Ask AI to earn App development

Phase 2: Testnet Launch and Alpha Season

Release and launch of Depai testnet v0.1

Test and optimization of validator, worker client, worker dashboard and ask to earn AI App

Target number of users: 1000+

Target number of workers: 100+

Phase 3: Testnet Season 1~4

OpenAI-compatible APIs

Validator election

New UI design implementation

Release of Depai testnet v0.9

Global marketing initiatives

Target number of developers: 10+

Target number of AI applications: 5+

Target number of users: 10,000+

Target number of workers: 5,000+

Target number of validators: 50+

Phase 4:Mainnet Beta Launch and Season 5 to 8

Release of Depai mainnet beta v1.0

Mainnet performance optimization

Target number of developers: 100+

Target number of AI applications: 50+

Target number of users: 100,000+

Target number of workers: 50,000+

Target number of validators: 500+

Phase 5: Mainnet Beta Optimization and Season 9 to 10

Continuous optimization of the mainnet beta

Generate advertising revenue

Target number of developers: 200+

Target number of AI applications: 500+

Target number of users: 1 million+

Target number of workers: 100,000+

Target number of validators: 1,000+

Target advertising revenue: 5 million+