Cluster Protocol × Nebulai: Scaling Decentralized AI Compute and Agent Execution
Dec 19, 2025
2 min Read
Why Decentralized AI Needs More Than Just Models
As AI systems become more agentic and autonomous, one constraint keeps resurfacing: compute.
Running AI agents, executing inference workloads, and coordinating multi-step AI workflows at scale requires more than centralized cloud resources. It demands infrastructure that is:
- distributed by design,
- resilient to single points of failure,
- and capable of scaling dynamically as demand grows.
This is where decentralized AI infrastructure becomes critical and where the collaboration between Cluster Protocol and Nebulai fits naturally.
Shared Direction
Cluster and Nebulai are both building core layers of the decentralized AI stack, but from complementary angles:
- Cluster focuses on AI orchestration, managing models, agents, and workflows on verifiable, privacy-aware infrastructure.
- Nebulai focuses on decentralized compute, aggregating idle hardware into a distributed execution network capable of handling AI workloads at scale.
Together, the partnership strengthens the foundation required to run AI agents and compute-heavy workloads in a truly decentralized environment.
Core Synergies
Expanding Decentralized Compute Capacity for AI Workloads
Nebulai operates a decentralized compute network that pools distributed hardware resources into a shared execution layer.
Cluster, on the other hand, requires scalable compute to support AI models, inference pipelines, and agent workflows.
Through this partnership:
- Cluster's AI workloads can leverage Nebulai's distributed compute network to scale execution beyond isolated environments.
- Nebulai's compute network gains real AI demand from agent-based and model-driven workloads orchestrated by Cluster.
This creates a practical alignment: compute supply meets AI execution demand, without relying on centralized cloud providers.
Distributed Execution for AI Agents
Cluster's AI agents are designed to operate across complex workflows, monitoring data, triggering actions, and coordinating logic across systems.
Nebulai's distributed execution layer enables these agents to:
- offload compute-intensive tasks,
- execute parallel workloads across multiple nodes, and
- operate with greater resilience and scalability.
Rather than running agents in isolated environments, this collaboration enables distributed agent execution, where different components of an AI workflow can be executed across a decentralized network.
What This Enables
For Builders
- More scalable environments to deploy AI agents
- Better performance for compute-heavy AI tasks
- Reduced dependency on centralized infrastructure
For the DeAI Ecosystem
- Stronger foundations for agent-based applications
- A clearer separation between orchestration (Cluster) and execution (Nebulai)
- Infrastructure that supports AI systems operating continuously at scale
This partnership is not about abstract experimentation, it's about making decentralized AI practical at runtime.
About Nebulai
Nebulai is a decentralized AI compute network that aggregates idle hardware resources into a distributed execution layer.
By coordinating workers, verifiers, and delegators, Nebulai enables scalable and permissionless compute for AI workloads across a decentralized network.
About Cluster
Cluster is the decentralized AI infrastructure powering the Liberation Engine for Internet Capital Markets.
It provides verifiable compute (PoAC), privacy-preserving execution (FHE/ZK), and modular AI orchestration, enabling developers to turn natural-language prompts into production-grade, tokenized dApps via CodeXero, Cluster's AI-native IDE.