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August 21, 2024 · 4 min · SQD Team

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

Case Study AI Ecosystem
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 on-chain 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.”

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