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FAQ

Your Questions About SPREAD, Answered

Understand how SPREAD supports engineering workflows across every product lifecycle phase with accurate, connected data.




SPREAD’s Agentic Engineering Intelligence is an AI-driven, federated system designed for engineering teams. It consists of three core layers:

  1. Rapid Data Ingestion – Smart connectors integrate structured and unstructured data from CAD, PLM, ERP, IoT, and other sources into the Engineering Intelligence Graph.

  2. Product Twin (PT) – A federated Knowledge Graph that contextualizes data across the product lifecycle, providing engineers with a unified, queryable data model.

  3. Action Cloud – AI-driven automation and analytics enable engineers to conduct compliance checks, optimize requirements, and analyze dependencies efficiently.

This architecture transforms raw engineering data into context-aware, AI-actionable knowledge, reducing manual effort and improving decision-making.

SPREAD’s Engineering Intelligence Graph (EI Graph) is a federated supergraph that unifies structured and unstructured product data across domains (R&D, Production, Aftermarket).
It leverages:

  • GraphQL-based schema to standardize data models.

  • Subgraphs optimized per domain, aggregated into a unified, scalable supergraph.

  • Automated AI-assisted data mapping to integrate diverse engineering data sources.

This enables cross-domain insights, real-time querying, and advanced analytics, making complex product data machine-readable and actionable. If you like to learn more about it, please watch this video: https://www.spread.ai/resources/knowledge-hub/how-we-use-a-graphql-schema-as-a-contract-to-efficiently-build-applications

Yes. SPREAD provides out-of-the-box connectors, API integrations, and graph federation to ingest data from CAD, PLM, ERP, and IoT systems. Features include:

  • Declarative data mapping – Standardizing heterogeneous data formats.

  • Real-time synchronization – Ensuring up-to-date insights.

  • Federated query capabilities – Allowing seamless interaction with external data sources.

SPREAD enhances existing tool chains by unifying, structuring, and contextualizing data, eliminating silos.

SPREAD integrates and analyzes diverse product data across the entire lifecycle. This includes CAD design data, engineering specifications, production metrics, test results, maintenance logs, and real-world usage feedback.

By unifying structured and unstructured data from multiple sources, SPREAD creates a comprehensive, interconnected view that enables engineers to understand complex dependencies, make data-driven decisions, and optimize product development and support processes.

EI Agents are AI-driven routines operating within SPREAD’s Engineering Intelligence Graph. They can be taught to automate engineering tasks by interpreting queries, accessing structured and unstructured data, and providing validated, context-aware insights.

These agents streamline workflows, enhance data mapping, and support high-value tasks like requirements analysis, error pattern detection, and specification generation.