Chutes

About Chutes

Chutes (TAO Subnet 64) delivers serverless AI inference infrastructure on Bittensor, enabling developers to deploy and run models at scale without managing GPUs or provisioning compute resources.

Its platform simplifies AI deployment by handling scaling, infrastructure management, and billing automatically. Developers can launch models with minimal configuration, allowing them to focus on application logic rather than backend infrastructure.

By providing serverless inference as a native subnet capability, Chutes lowers the barrier to building production-grade AI systems on Bittensor.

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Strategic Alignment

Desearch (SN22) provides decentralized real-time search and data intelligence.

Chutes (SN64) provides scalable, serverless inference infrastructure.

Modern AI systems require both: live information access and efficient model execution.

This partnership aligns the data layer and the inference layer of decentralized AI. By combining search-augmented retrieval with serverless model deployment, SN22 and SN64 strengthen the full application stack on Bittensor.

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What This Unlocks

Together, Desearch and Chutes enable:

• Search-augmented AI agents deployed in minutes

• RAG pipelines powered by live web and social data

• Seamless scaling from prototype to production

• Cost-efficient inference using pay-per-use infrastructure

• Reduced operational complexity for developers

Builders can now integrate real-time search and serverless inference without stitching together multiple infrastructure solutions.

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Technical Collaboration

Desearch powers real-time data retrieval.

Chutes powers serverless inference.

Together, they create a unified pipeline where live search feeds directly into scalable model execution.

The collaboration focuses on optimizing search-to-inference workflows, shared developer tooling, and pre-built templates for RAG and agent-based systems.

The goal is to remove infrastructure friction while maintaining a fully decentralized architecture.

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Ecosystem Impact

This partnership reduces friction for AI builders on Bittensor.

Instead of managing GPUs, scaling logic, and separate data pipelines, developers can focus on building intelligent applications.

By aligning decentralized search with serverless inference, SN22 and SN64 strengthen the developer experience and accelerate ecosystem adoption.

The result is a more accessible, scalable, and production-ready decentralized AI stack.

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Looking Ahead

The integration between Desearch and Chutes is ongoing.

Future initiatives may include:

• Deeper API-level integration

• Shared SDK releases

• Pre-configured deployment templates

• Optimized data pipelines combining real-time retrieval with inference execution

As both subnets evolve, the collaboration will continue to expand the capabilities available to builders across Bittensor.

The long-term vision is clear: seamless interoperability between data access and model execution layers within a fully decentralized AI ecosystem.