Case Study: How Guru Network powers its AI processors with data from SQD

· 4 min · SQD Team
Case StudyAIEcosystem
Case Study: How Guru Network powers its AI processors with data from SQD

Fact Sheet

Guru Network Overview: A multichain AI compute layer enabling dApps and users to integrate AI agents into their workflows for process automation.

Critical Feature: Multichain indexing

SQD Application: Aggregating on- and off-chain data from multiple sources

Unique Advantage: Access to EVM and non-EVM chains' data

How Guru Network Leverages SQD

Guru Network operates at the intersection of AI and blockchain, democratizing AI-powered process automation. The platform comprises:

  • Flow orchestrator (managing Business Process Automation and AI Processes)
  • Data warehouse (storing data for AI processes)
  • BBPA engine event bus (network-native oracle)
  • AI compute oracle (predictive analytics and decision-making enhancement)

The Data Challenge

Guru Network initially built their own infrastructure starting in 2020, creating the DexGuru indexer (a fork of ethereum-etl) to address unreliable RPC providers and DEX analytics needs.

"Effectively, we've built a Web2-style caching layer on top of Web3"

SQD Integration

Following discussions at EthDenver, Guru integrated SQD's data lake for comprehensive onchain data access. The warehouse processes this information, cleaning, normalizing, and compressing it for AI processors.

"We are utilizing the SQD SDK to fetch historical and real-time data"

Collaboration Results

The teams found smooth integration with clear documentation. Guru noted: "Working with the SQD Team has been smooth and straightforward."