Enterprise AI for Aerospace & Defense Engineering
The interface is the easy part. The hard part is indexing decades of engineering, quality, and ITAR-marked data, secure, traceable, and governed. That’s where Sinequa fits: the knowledge layer that grounds AI Wingmate and your agents, not another assistant competing with them.
Wanting control over your AI, the IP, the roadmap, what it can reach, is exactly right for an environment like yours. AI Wingmate has already processed 200,000+ pages, and your Engineering & Quality assistant is trained on 30+ years of nonconforming-hardware data. The interface was never the hard part.
Reaching the knowledge behind it is. Your highest-value data, ITAR-marked design and test data across DPT and Edison Works, the quality records that decide part disposition, decades of program history in Teamcenter, is exactly what a general Azure index can’t safely hold. So even a strong assistant answers from what it can reach, not the engineering core.
Sinequa is the retrieval layer for that content: security-trimmed, traceable, deployed inside your boundary, and exposed to AI Wingmate, Copilot, and your agents through MCP. Not replace vs. keep, just grounding the AI you already run in the knowledge it can’t reach today.
The interface is the easy part. These are the capabilities that decide whether what you’ve built can be trusted, from LEAP and GEnx sustainment to next-gen work at Edison Works.
Drawings, requirements, test and verification records, MRB history, service records, program documentation, and supplier data live in PLM, ERP, quality systems, and document repositories, not the collaboration layer.
A connector says “supported.” Real indexing means reading the engineering artifact itself, 2D/3D CAD and scanned technical documents, so an engineer can trust the answer, trace it to source, and act on it in a part evaluation.
Document-level, attribute-based access controls inherited from your source systems and enforced on every query, across billions of documents. An answer never exposes what a user isn’t cleared to see. Full audit trail of any action.
On-premise, hybrid, or fully air-gapped. ITAR-ready. For classified and export-controlled programs across Defense & Propulsion Technologies, this is where most platforms and general-cloud builds stall.
Part numbers, requirement IDs, engine program nomenclature, AS9100 and MIL-SPEC terminology, FAA/EASA certification language. Generic relevance and engineering relevance are not the same thing.
The knowledge layer feeds whatever sits on top, AI Wingmate, your own interface, any model. A2A and MCP ready. You keep control of the front end; Sinequa keeps the retrieval reliable underneath it.
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 the retrieval layer that grounds the AI you already run.
Watch how Sinequa indexes drawings, requirements, nonconformance, and service records across systems: security-trimmed, traceable, and exposed to AI Wingmate, Copilot, or any agent through MCP. Ready to see it in your environment?
Book a custom demo →
These are the multi-step questions your engineers ask every day, where the answer is buried across design, requirements, test, and supplier systems. Whatever AI you build has to answer them. That depends entirely on what it can retrieve.
Comparable cases returned with disposition history, quality records, and traceable evidence in seconds.
Affected requirements, linked test procedures, and coverage gaps mapped across the program baseline against AS9100 and FAA/EASA references.
Records assembled across MRO systems and program data, cited to source, to speed shop turnaround and on-time delivery.
Ranked, sourced, and traceable, directly relevant to backlog throughput and program schedule.
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 300+ file formats, including 2D/3D CAD. Connectors inherit and enforce your existing permissions, so every engineer and every AI agent sees only what they’re authorized to see. Deployable on-premise, hybrid, or fully air-gapped inside your ITAR boundary, with no dependency on external services.
A conversation about your knowledge architecture: where you’re already strong, and where a proven retrieval layer could be the exact accelerator you need. A working session on GE Aerospace’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.
