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Connect Your Digital Thread with GenAI
According to CIMdata, engineers waste 15-30% of their time simply searching for product information — part specifications, design files, test procedures, maintenance records — that is scattered across PLM systems, ERP, MES, CAD repositories, and service platforms that were never designed to share data with each other. For a 500-person engineering organization, that represents tens of thousands of hours per year spent on search instead of design, innovation, and problem-solving. And for service teams managing complex field operations, fragmented MRO data translates directly into longer resolution times, higher costs, and lower customer satisfaction.
In this on-demand webinar, Jim Brown, President of Digital Innovation Research at Tech Clarity, and Jeff Evernham, Chief Product Officer at Sinequa, explain how search-powered GenAI changes this equation — and how leading manufacturers including Alstom, Siemens, and Airbus are already using it to accelerate product development and improve service operations.
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What You’ll Learn in This Webinar
How much time engineering and service teams actually lose to search Jim Brown shares research quantifying the productivity cost of fragmented digital thread data — what percentage of an engineer’s day is consumed by locating, retrieving, and preparing product information rather than using it. The numbers are significant enough that eliminating even a fraction of this waste represents a measurable ROI for any large manufacturing organization.
Why digital thread data is so hard to access despite heavy PLM investment Most manufacturers have invested substantially in PLM systems, ERP, MES, and CAD platforms. Yet the data in these systems remains siloed. This webinar explains the structural reasons why — different data models, access controls, search interfaces, and user experiences across each system — and why traditional integration approaches have failed to solve the findability problem at the user level.
How search-powered GenAI reduces product development time and accelerates time-to-market The combination of enterprise search and Retrieval-Augmented Generation (RAG) gives engineers a single natural language interface to all product data across every connected system — with AI-generated answers grounded in verified, cited source documents rather than generic model outputs. Alstom used this approach to eliminate redundant parts manufacturing across a 3-million-part catalog, saving $40M plus an additional $6M through automated proposal generation. Siemens achieved 30% faster information discovery for technical teams.
How AI-powered search unlocks service intelligence for better MRO performance Service and maintenance teams face a parallel version of the same problem: troubleshooting procedures, repair histories, bills of materials, and service bulletins scattered across disconnected systems. This webinar demonstrates how search-powered GenAI gives field and depot technicians instant access to the right information for complex maintenance activities — improving first-time fix rates, reducing unplanned downtime, and increasing MRO profitability.
Why This Webinar Matters Now
The digital thread concept has been discussed in manufacturing for over a decade — but for most organizations, it has remained more aspiration than operational reality. Product data exists in theory across the lifecycle, but in practice it lives in a dozen disconnected systems that engineers must navigate manually. GenAI changes the economics of solving this problem: rather than requiring years of integration work to centralize data in a single repository, search-powered GenAI creates a unified access layer on top of existing systems — giving every engineer, technician, and knowledge worker a single intelligent interface to all of it, without displacing the source systems that teams already rely on.
This webinar, grounded in independent research from Tech Clarity and live platform demonstrations from Sinequa, provides the business case and technical architecture framework that manufacturing technology leaders need to evaluate search-powered GenAI as a practical next step in their digital thread strategy.
Frequently Asked Questions (FAQ)
The digital thread is the connected flow of product data across the full lifecycle — from design and engineering through manufacturing, quality, maintenance, and field service. In theory, it gives every stakeholder access to the same authoritative product information at every stage. In practice, the systems that make up the digital thread — PLM, ERP, MES, CAD repositories, service platforms, and maintenance records — each have different data models, access interfaces, and search experiences. Connecting them requires either expensive, brittle point-to-point integrations or a new access layer that understands all of them simultaneously. Search-powered GenAI provides that access layer without requiring data migration or system replacement.
Search-powered GenAI combines enterprise search — which indexes and understands content across all connected systems simultaneously — with Retrieval-Augmented Generation (RAG), which retrieves relevant information from those systems before generating an AI response. The result is a natural language interface that engineers and technicians can query in plain language — “What is the testing procedure for this component?” or “What are all the past repair records for this assembly?” — and receive AI-generated answers that cite the specific documents in the source systems where the information lives. This is different from generic AI tools, which have no access to proprietary manufacturing data and generate responses from public training data instead.
Alstom eliminated redundant parts manufacturing across a 3-million-part catalog using Sinequa’s AI-powered search, saving $40M — plus an additional $6M through automated proposal generation. Siemens reported 30% faster information discovery for technical teams. Airbus deployed the platform for over 700 engineers worldwide to provide a single secure access point to all engineering data. Beyond engineering, manufacturers with large in-service fleets — like Airbus Helicopters, which supports 12,000 helicopters — use the same platform to give service agents 360° views of customer cases and proactive repair recommendations, directly improving resolution speed and customer satisfaction.
Sinequa connects to the full range of digital thread systems through 200+ ready-to-use connectors: PLM platforms including Siemens Teamcenter and PTC Windchill, ERP (SAP), MES, MRO systems, CAD repositories, MBSE platforms, CRM, SharePoint, Microsoft Teams, OneDrive, Box, Confluence, and file systems. All source system access controls are inherited and enforced at the document level — ensuring engineers and technicians see only the product data their role and project authorization permit. The platform handles both structured data (part catalogs, bills of materials, transaction records) and unstructured data (technical documents, emails, maintenance reports) simultaneously, without requiring separate queries to separate systems.
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