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Sinequa’s Manufacturing Executive Summit
I-Powered Search, RAG, and the Cognitive Digital Thread
The manufacturing world is undergoing a seismic shift. As competition intensifies, organizations must connect industrial data with collaborative knowledge to stay ahead. With the rapid acceleration of AI, and especially Generative AI, manufacturers now have unprecedented opportunities to boost engineering productivity, streamline maintenance and support, accelerate product development, and deliver superior customer experiences.
That’s why Sinequa is hosting the Manufacturing Executive Summit: a virtual gathering designed to unite forward-thinking leaders who are transforming their operations with AI-powered search, RAG, and the Cognitive Digital Thread. Hear firsthand how industry innovators are driving measurable business outcomes with Sinequa’s advanced technology.
Full Summit Agenda
- Analyst Keynote: Extracting Insight from the Digital Thread: AI Trends & Industry Enablers Peter Bilello, President & CEO, CIMdata — Independent research on AI adoption trends in manufacturing, the state of the digital thread, and the industry enablers that separate successful AI deployments from stalled experiments.
- The Cognitive Digital Thread: Where Industrial Data and AI Meet Jeff Evernham, VP of Strategy & Solutions, Sinequa — How AI-powered search and RAG connect PLM, ERP, MES, CAD, DMS, and legacy systems into a unified knowledge layer that every engineering, manufacturing, quality, maintenance, and service team can access from a single entry point.
- Live Product Demonstration: Searching Across the Digital Thread — Search + RAG + GenAI in Action Sommy Boucansaud, VP of Customer Solutions, Sinequa — A real-time demonstration of Sinequa’s enterprise search and RAG platform querying across connected manufacturing systems, with AI-generated answers cited from source documents, in natural language.
- Customer Testimonial: JAFAR — A GenAI-Powered Application for Rapid Knowledge Access TotalEnergies — How one of the world’s five largest energy companies built JAFAR, a multilingual GenAI assistant powered by Sinequa, to give field engineers and operations teams instant access to Return of Experience knowledge across four languages and multiple global sites.
- Advancing AI Assistants: Sinequa’s Product Roadmap Jeff Evernham, VP of Strategy & Solutions, Sinequa — Where AI assistants in manufacturing are heading: agentic AI capabilities, autonomous multi-step workflows, and the platform evolution that moves enterprise AI from answering questions to taking governed actions.
Watch the full video
What Manufacturing Technology Leaders Take Away from This Summit
The summit is structured to address the three questions manufacturing CIOs and engineering IT directors consistently bring to enterprise AI evaluations:
Is the market data credible? Peter Bilello’s CIMdata keynote provides the independent research foundation — including the 15–30% engineer time waste estimate and AI adoption trends across PLM and digital manufacturing — that separates a vendor’s claims from validated industry benchmarks.
Does it work in a real manufacturing environment? TotalEnergies’ JAFAR deployment is a production GenAI application — not a pilot, not a proof of concept — operating across a 1,700-person refinery and expanding globally. The challenges TotalEnergies solved (multilingual knowledge access, ROE database retrieval, field engineer adoption at scale) are the same challenges every complex industrial operator faces.
What does the platform actually do? Sommy Boucansaud’s live demonstration shows Sinequa’s search + RAG + GenAI platform querying across PLM, ERP, MES, CAD, and DMS data simultaneously — with AI-generated answers grounded in cited source documents, not model hallucination.
Individual Sessions Available Separately
Each major summit segment has its own dedicated replay page for teams who want to focus on a specific topic:
Frequently Asked Questions (FAQ)
The Manufacturing Executive Summit is Sinequa’s flagship virtual event for manufacturing technology leaders — CIOs, VP Engineering, digital transformation directors, engineering IT heads, and industrial AI program managers. The 2024 summit combined an independent analyst keynote from Peter Bilello (President & CEO of CIMdata, the world’s leading PLM research firm), a live TotalEnergies customer testimonial on JAFAR (their Sinequa-powered multilingual GenAI assistant), a live product demonstration of search + RAG + GenAI across connected manufacturing systems, and a forward-looking product roadmap session from Jeff Evernham. The full replay is available on this page, with individual session replays available separately.
JAFAR (Generative AI for Return of Experience) is a multilingual GenAI assistant built by TotalEnergies on Sinequa’s enterprise AI platform. It connects field engineers and operations teams with Return of Experience (ROE) knowledge — historical incident records, failure analyses, and resolution documentation — across four languages (French, Dutch, German, English) and multiple sites. The summit’s TotalEnergies customer testimonial demonstrated a production deployment, beginning at the refinery with 1,700 employees, that directly addresses one of the most costly recurring problems in industrial operations: incidents that repeat because the records documenting how previous incidents were resolved cannot be easily retrieved by field teams.
The Cognitive Digital Thread — Sinequa’s AI-powered search and RAG foundation connecting PLM, ERP, MES, CAD, DMS, and legacy systems — is the retrieval infrastructure that makes agentic AI in manufacturing trustworthy. Jeff Evernham’s product roadmap session at the summit addressed this directly: AI agents that can autonomously monitor parts catalogs for redundancy, surface maintenance alerts proactively from connected MRO data, or cross-reference new regulatory requirements against technical documentation are only reliable when the retrieval layer beneath them is accurate, source-cited, and connected to authorized enterprise data. The summit roadmap session outlines how Sinequa is extending from AI assistants that answer questions to AI agents that take governed, multi-step actions — built on the same Cognitive Digital Thread foundation.
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