Enterprise AI for Stanley Black & Decker Engineering
A major PLM migration is the moment to fix fragmented engineering data, not carry it forward. Sinequa reaches the CAD and design knowledge scattered across your PLM systems, SharePoint and SQL databases. Indexed at depth, enriched, deduplicated, security-trimmed.
In design and engineering, the answers your teams need aren’t in Teams chats or M365 files. They’re inside 100,000+ CATIA V5 drawings, Windchill part records, NX and CREO models, SOPs on SharePoint, and SQL databases across the business. Copilot reaches the collaboration layer, it was never built to read a 2D drawing or resolve a duplicate sub-assembly. And manual enrichment against SOPs is slow, ~50 categories deep, and error-prone; the internal AI attempt hallucinated.
3DX go-live doesn’t fix this, it inherits it. Move as-is and you carry duplicate parts and thin records into the new platform, while everything outside 3DX sits behind a closed door.
Sinequa fixes both ends. Before cutover: extract structured attributes straight from your CAD drawings, enrich part records at scale, and flag duplicates across the portfolio, grounded and traceable, not hand-keyed and not hallucinated. After go-live: a white-box search layer over everything 3DX indexes and everything it doesn’t, so no engineer re-engineers a part that already exists.
Demos and connector lists rarely surface the differences that decide a real deployment.
CATIA V5 drawings, Windchill part records, NX and CREO models, SOPs on SharePoint, SQL databases, and email, not just the Microsoft 365 collaboration layer.
A connector says “Windchill: supported.” Real indexing means reading the drawing itself, geometry, annotations, attributes, and grounding every answer in that source.
On-premise in your data center today; private cloud or Azure tomorrow. For SBD’s IP and an active PLM migration, where your data lives is a requirement, not a preference. The platform adapts to your infrastructure roadmap, not the other way around.
Global engineering teams work across languages and sites. Knowledge should surface regardless of where, or in what language, it was authored.
Related parts, BOM linkages, cost data, design history surfaced instantly. No manual PLM navigation. New engineers get context on day one instead of re-engineering existing parts.
Document-level access enforced at query time, so an answer never exposes what a user isn’t cleared to see. A full audit trail for every retrieval, the discipline your AI governance team already expects, applied to engineering data at enterprise scale.
These requirements are drawn from the patterns we see across the industry’s most complex deployments. Read the State of Enterprise Agentic AI 2026 →
See how Sinequa indexes the systems of record Stanley Black & Decker’s engineering knowledge lives in.
Watch how engineering teams query drawings, part attributes, and design history and get answers an engineer can trust. Ready to see it in your environment?
Book a custom demo →
These aren’t search queries. They’re the multi-step questions your engineers ask every day, where the answer is buried across CATIA, Windchill, and SOPs. Each one below shows the question and what Sinequa returns: a quick, reliable answer that saves weeks.
Candidates returned with Matching and near-matching parts surfaced across Windchill and legacy CAD, ranked by similarity.
A single Part 360 view assembled across PLM, CAD, and SQL in seconds.
Structured attributes pulled from the drawing itself, source-linked and reviewable.
Prior designs, related SOPs, and the discussion around them, surfaced from CAD, SharePoint, and email.
Backed by independent recognition from Gartner, Forrester, and SPARK Matrix™.
$0M
Productivity gains
$0M
Warranty avoidance
$0M
Development savings
Measured over three years.
NEW STUDY
The Forrester Total Economic Impact™ Of Sinequa AI-Powered Search
An independent Forrester Consulting study, built on a composite $20 billion enterprise, quantifies what a governed enterprise search and AI layer returns over three years: 299% ROI, $22.4M net present value, and payback in under six months. Based on interviews with five decision-makers across chemicals, manufacturing, life sciences, transport, and aerospace and defense.
With Sinequa, our engineers can ask a complex, multi-part question and get a concise answer plus the underlying evidence. That’s a game-changer for design, warranty, and failure analysis.
Oliver Scott Beard Principal Technical Architect – AI Systems, Cummins
Sinequa connects to 200+ enterprise applications and 500+ file formats, including 2D and 3D CAD, with no custom coding. From Windchill and Dassault 3DEXPERIENCE to CATIA V5, NX, CREO, and TeamCenter and across SharePoint, SQL, and Microsoft 365, Sinequa indexes and enforces your existing permissions, so every engineer and every AI agent sees only what they’re authorized to see.
A conversation about your current build: what’s working, where it’s stalling, and what a native-connector path looks like. A working session on Stanley Black & Decker’s toughest knowledge problems.
Trusted by over 2,000 customers across 40 countries.
ChapsVision is a global leader in agentic AI and data solutions. Trusted by over 2,000 customers across 40 countries, ChapsVision delivers industry-specific software solutions powered by agentic AI to meet the complex needs of data-intensive sectors. Its innovative and scalable Data & AI platform is powered by proven technology enablers that accelerate data acquisition, preparation, and analysis.
Driven by significant R&D investments in large-scale data and AI and supported by a targeted strategy of acquisitions and international expansion, ChapsVision has rapidly established itself as the trusted partner in agentic AI for business and government organizations around the world.
