VaaniAI

Vaani AI Subnet Proposal — Brief Description

Vaani AI is a production-ready Bittensor subnet designed to build decentralized voice synthesis infrastructure through competitive text-to-speech (TTS) intelligence markets. The subnet enables miners to provide high-quality voice generation services while validators continuously evaluate outputs using automated benchmarking metrics such as naturalness (MOS estimation), speaker similarity, multilingual consistency, latency, and robustness. Emission rewards are distributed based on measurable performance through Yuma consensus, ensuring that higher-quality models receive greater incentives.

By replacing centralized voice AI providers with an open, competitive network, Vaani AI reduces vendor lock-in, improves transparency, and distributes control over voice data and infrastructure. The system introduces strong economic alignment between miners and validators, promotes continuous model improvement, and creates a scalable marketplace for decentralized voice generation services across applications such as AI agents, accessibility tools, content creation, and enterprise voice systems.

Progress During Hackathon

During the hackathon period, the Vaani AI team focused on designing and validating a production-ready architecture for a decentralized voice synthesis subnet on Bittensor. The core progress included defining the subnet’s incentive and emission mechanics aligned with Yuma consensus, establishing measurable evaluation frameworks for voice quality, and designing miner–validator interaction workflows.

The team developed detailed system architecture covering miner pipelines for text-to-speech inference, validator evaluation infrastructure, prompt randomization mechanisms, and automated benchmarking using metrics such as MOS-based naturalness scoring, speaker similarity analysis, multilingual testing, latency measurement, and robustness evaluation. Additionally, failure modes such as prompt memorization, validator collusion, and emission gaming were analyzed with mitigation strategies integrated into the subnet design.

Alongside technical design, significant progress was made in defining the economic model, validator permit dynamics, and long-term sustainability strategy transitioning from emission-driven incentives toward real inference demand. The hackathon milestone resulted in a comprehensive subnet blueprint ready for implementation and early-stage deployment within the Bittensor ecosystem.