The African deAI Ecosystem

A market for machine intelligence where subnets compete on usefulness and demand.

African relevance: Strongest deAI reference point for investors tracking protocol economics.

A consolidation story around open-source AI and long-horizon ecosystem coordination.

African relevance: Useful for readers tracking model distribution and alliance-level capital flows.

Distributed GPU infrastructure with a direct link to graphics, inference, and AI workloads.

African relevance: Relevant where African users need access to global compute and creator-led demand.

Data exchange rails for datasets, permissions, and AI-market liquidity.

African relevance: Best understood as a data infrastructure play rather than a consumer AI product.

Decentralised cloud compute for teams that need affordable GPU and general-purpose hosting.

African relevance: Important where cost-conscious African builders need alternatives to hyperscalers.

GPU aggregation for inference and training workloads across distributed infrastructure.

African relevance: Relevant to the hardware supply story underpinning decentralised AI adoption.

An AI service marketplace where developers publish, discover, and monetise AI agents on-chain.

African relevance: Foundational to the ASI Alliance thesis and one of the earliest deAI protocol experiments.

Decentralised ML compute network allowing anyone to contribute compute to model training jobs.

African relevance: Directly addresses the training compute bottleneck that constrains open AI development.

Protocol for deploying and running autonomous AI agents across decentralised infrastructure.

African relevance: Increasingly relevant as agentic AI becomes the dominant deployment model for deAI.

On-chain AI inference layer bringing model execution directly into smart contract logic.

African relevance: Bridges the gap between blockchain-native applications and AI model outputs.