Data Infrastructure for Engineering AI
Engineering data is fragmented across simulation, test, manufacturing and fleet systems. Key Ward turns that chaos into reusable workflows, governed datasets and AI-ready infrastructure.
Used by engineering teams at
Used by engineering teams at
/ problem
Industrial AI Fails Without Engineering Data Infrastructure
Simulation, test, and manufacturing data are scattered across files, scripts, and disconnected tools. As a result, engineering analyses are repeated, AI models cannot be reproduced and valuable knowledge is lost.
3D meshes
Multi-physics
solver specific, not compatible for modern AI
1D signals
CSV
HDF5
SQL
Process Logs
Quality Data
Time-Series
IoT Streams
Fragemented Workflows
Fragmented Engineering and ML Stack
Outcome
Reproduceable Workflows
Key Ward Integrates & Augments with your Existing ML Stack
Reusable Engineering Intelligence
Without Key ward
5%
of engineering organizations move AI/machine learning from pilot to production at scale
with key ward
100%
AI scales across engineering teams and programs
/ why now
Engineering data is growing exponentially, while data & workflows remain manual and fragmented across teams and projects
Key Ward provides a standardized engineering data infrastructure that structures engineering data into reproducible pipelines, making simulation, test, and manufacturing systems interoperable and AI-ready.
Product complexity is increasing
Simulation and testing data volumes are exploding, but remain fragmented
Data platforms store data. AI platforms train models. But neither solution structures engineering data for reuse
Companies struggle to scale & integrate AI across engineering programs
Engineering Data Infrastructure Is Critical
/ Positioning
The Missing Infrastructure Between Engineering Data and AI
Most internal stacks treat engineering data as generic files, but engineering workflows require experiment lineage, simulation metadata and configuration tracking. Key Ward provides a domain-specific layer that makes engineering data interoperable and AI-ready.
/ SOLUTION
Key Ward Powers AI-driven Engineering With Unified & Collaborative Data Infrastructure
Engineering organizations are moving from fragmented, underused data to structured intelligence through a new infrastructure layer that connects engineering systems to advanced and reusable analytics and AI.
Data Connect
Data Hub
Workflow Engine
Model Engine
Knowledge Engine
60%
faster time to insight vs. manual data preparation workflows
90%
reduction in simulation and compute costs
4–5
hours saved per cycle vs. manual data handling
70%
faster RFQ resolution versus traditional engineering workflows
/ how it works
How Engineering Data Becomes AI-Ready
Connect your engineering systems
Extract manufacturing, simulation, and testing data from proprietary engineering sources.
Structure reusable engineering data assets
Transform & process fragmented engineering data into structured, queryable datasets that can be reused across teams and projects.
From one-off analysis to reusable engineering workflows
Instead of rebuilding analysis pipelines for every investigation, turn engineering investigations to reusable workflows. Failure analysis, design exploration, or modeling pipelines can be applied to new datasets, new products and new programs across the organisation.
Run your AI stack at scale
Deploy Key Ward in your cloud or behind your firewall and run your own AI models or open-source frameworks on structured engineering data without replacing your existing tools.
/ lifecycle
Engineering Data Infrastructure Across the Full Product Lifecycle
From concept to post-launch, Key Ward powers data-driven engineering workflows.
Concept
Leverage Historical Performance Data
Make smarter decisions earlier in the design cycle by identifying technical requirements and performance trade-offs instantly using historical simulation and test datasets.
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Autoneum reached optimal acoustic performance for an advanced material using structured data and a repeatable workflow
Modeling
Data-Driven Modeling
Accelerates simulation workflows, reduces compute time, and provides engineers with trustworthy, interpretable models.
FEV Accelerates CFD Convergence with Reduced Order Modeling
Validation
Centralized Validation Data
Integrates simulation and test data in one environment enabling consistent, repeatable validation workflows across digital and physical data. Anomaly detection and prediction accuracy is nearly identical to conventional simulation in a fraction of the time.
Carnot transformed its data workflows from manual and fragmented to automated and reusable
Production
Optimized Performance Across Variable Conditions
Verifies that models perform reliably across changing environmental and operational conditions. Leverages production and sensor data to optimize product performance and manufacturing processes faster than conventional methods.
Tier 1 Supplier Reduces Scrap and Improving Manufacturing Quality with Data-Driven Production Analytics
Post-Launch
Continuously Improving Systems
Ongoing feedback loops leverage design, testing, and field data from systems in service to refine engineering models and improve next-generation builds.
Automotive OEM Accelerates Root Cause Analysis with Structured Plant and Field Data
/ Why Key Ward
Engineering teams across automotive, aerospace, and industrial manufacturing are using Key Ward
Works with your existing tools — no rip-and-replace
Run your own machine learning models or integrate open-source frameworks
Deploy behind your firewall or in your cloud
No data lock-in
$230K+
in annual savings vs. repetitive manual processing tasks
70%
reduction in turnaround time for full DoE studies
€0.5M
saved in scrap, energy and inefficiency
Leading Engineering Organizations Gain an Advantage with Key Ward
Modeling
“Key Ward reduced RFQ time from 1.5 months to days. And it’s got a great interface as well.”
Sr. Development Engineer Tier 1 Supplier
Validation
“We’ve eliminated 4–5 hours of manual data handling per cycle. Our engineers now go straight from test to insight because Key Ward auto-connects to our rigs, instantly structuring data for analysis and optimization.”
Sr. Development Engineer
Modeling
”Key Ward helped FEV turn simulation data into reusable engineering intelligence that enabled faster convergence, lower cost experimentation, and scalable CFD workflows.”
Lead CFD engineer
Concept
“What used to take days now takes minutes. We spend less time processing data and more time making decisions. We have clear visibility into the data that is being used to train our models.”
Dr. Thibault Lafont
Technical Expert, Acoustics
Post-Launch
“By connecting plant and field data with explainable AI, a leading automotive OEM moved from reactive troubleshooting to proactive, data-driven reliability engineering, turning post-launch data into strategic advantage“
Sr. Development Engineer
Modeling
“Key Ward helped our engineering program move beyond brute-force simulation using structured data and reduced order models to optimize aerodynamics faster, at a lower cost, and at scale"
Senior Aerodynamics Engineer
/ about
3,500 engineer-to-engineer conversations brought us here
We spent years at Porsche and BMW building simulation models. The models produced results, but the data behind them was never reused because it was scattered across formats that didn't talk to each other.
We founded Key Ward to solve this problem.
