As a top performer in BNB Chain’s MVB 7 program and backed by YZiLabs, Gata recently raised $4 million in seed funding led by notable VCs, including Gate Ventures, IDG Blockchain, Maelstrom Fund, Manifold, and others. With a growing community of over 800,000 users, Gata is pioneering decentralized AI infrastructure.

Data & compute centralization

Today’s AI is dominated by tech giants—OpenAI, Google, Meta, Microsoft, and Amazon—who control most high-quality training data and advanced models. Reports show over 60% of global AI compute resides in a handful of cloud providers, limiting participation and innovation.

Gata addresses these challenges by building decentralized AI infrastructure. Through its product matrix—GataGPT (Intelligent Interaction Layer), DataAgent (Data Generation Layer), and decentralized model inference and training technologies (Infrastructure Layer)—Gata supports the rapidly growing AI economy.

DataAgent: The decentralized AI-Driven data factory

Data is the fuel of AI, but traditional data production is labor-intensive and limits scalability. DataAgent transforms this by enabling users worldwide to contribute compute (home GPUs or edge devices), accelerating and automating dataset generation.

DVA DataAgent: Now live, it automates quality scoring for large-scale image-text pairs, feeding models like Stable Diffusion and GPT-4o. This automation boosts efficiency by over 100× compared to manual labeling.

Technical innovations & ecosystem benefits:

  • AI-Driven automated labeling: DataAgent uses AI to clean, generate, and validate datasets. By May 2025, it processed over 15 million multi-modal images.

  • Decentralized consensus validation: Contributions are recorded on-chain and only accepted after majority-node consensus, ensuring over 99.5% accuracy.

  • Elastic, scalable compute: Browser-based participation allows anyone to join, with over 300,000 nodes across 180 countries as of May 2025.

Key Scenarios:

  • Open-Source AI Data Engine: Partners with AI research institutions to deliver scalable, multilingual data streams—reducing training costs and democratizing research.

GataGPT: One smart hub for multi-model answers

GataGPT isn’t just a chatbot—it’s a hub connecting users, the real-world AI economy, and decentralized infrastructure. It integrates leading AIs (ChatGPT, Gemini, DeepSeek), ensuring every query receives diverse perspectives to reduce bias.

Technical architecture & core advantages:

  • Multi-Model Responses: Queries trigger simultaneous answers from several top AIs, overcoming single-model biases.

  • "GPT‑To‑Earn" Incentives: Users earn Gata Points by contributing conversation data, building a massive real-user conversation dataset—over 3.5 million entries by Q2 2025.

  • Privacy-First, On-Chain Storage: All data is encrypted and stored on BNB Greenfield. Users retain ownership and control, enabling anonymous, permissioned interactions.

Application scenarios:

  • Web3-Native AI Assistant: Provides strategy insights, code reviews, and analytics for DeFi, DAOs, and smart contracts.

  • Localized Minority-Language Assistants: Delivers culturally nuanced services in languages like Hindi, Thai, Vietnamese, and Arabic, with future fine-tuning by local developers.

Decentralized large-model inference and training

As the global AI economy nears trillion-dollar scale, large-model training and inference become critical infrastructure. Gata aims to build a fully decentralized infrastructure combining storage, cross-chain smart contracts and dynamic scheduling, enabling trillion-parameter models to run across decentralized GPUs—reducing cost, scaling elastically and resisting censorship.

Technical Architecture & Performance Highlights:

  • Decentralized Inference: Gata partitions models across geo-distributed GPUs, optimizing inter-node communication to approach centralized performance.

  • Decentralized Training: Trillion-parameter models train collaboratively via pipeline parallelism, with validator nodes ensuring gradient integrity. Training checkpoints and proofs are recorded on-chain for transparent incentive distribution.

  • Cost Efficiency: Gata’s approach cuts compute expenses by up to 95% versus centralized providers while scaling to enterprise-grade workloads.

Applications:

  • Global compute Network: Builds an open, elastic AI compute network with pay-per-use pricing metered in FLOPs.

  • Model Crowdfunding: Enables researchers to launch global training-compute-crowdfunding without upfront costs, democratizing large-model training.

Gata’s decentralized transformation of the AI industry

Gata’s core products—GataGPT, DataAgent, and Decentralized Inference & Training—represent a paradigm shift:

  • Returning Data Sovereignty: Token incentives and on-chain proofs empower individuals as data owners. By 2030, up to 30% of the global data economy could flow through decentralized platforms.

  • Open AI infrastructure: A unified, decentralized architecture breaks data silos and compute monopolies, offering equitable access. Gata plans to launch its GATA utility token in Q4 2025.

Roadmap: Decentralized AI infrastructure

Gata’s roadmap aims to reshape AI architecture into a globally distributed, censorship-resistant intelligence network—where every instance of training and inference is open and verifiable.

In Gata’s vision, the AI economy should be open and collaborative, supporting both centralized and decentralized models to ensure superintelligence evolves as humanity’s partner.

About Gata

Gata is a decentralized AI supercomputer — affordable and accessible to every AI team. Gata orchestrates planet-scale tensor flows across a global, permissionless compute grid for the most demanding AI workloads. Built for AI at any scale, Gata makes frontier intelligence universally accessible at a dramatically lower cost, unlocking its full transformative impact.