Data Infrastructure for Engineering AI
Engineering data is fragmented across simulation, test, manufacturing and fleet systems. Key Ward turns that chaos into governed datasets and reusable AI-ready workflows, so your engineers go from data to decisions in minutes, not days.
"We generated data across seven simulation and test environments. Key Ward connects all of it automatically; structured, queryable, and ready for Al/ML with dashboards that give stakeholders instant visibility. Groundbreaking for any data-drive engineering team. We are already seeing fruits and can't wait until we are fully migrated with all our data in one place!"
”Key Ward helped FEV turn simulation data into reusable engineering intelligence that enabled faster convergence, lower cost experimentation, and scalable CFD workflows.”
“Key Ward reduced RFQ time from 1.5 months to days. And it’s got a great interface as well.”
“The missing link between your data and your reporting. Key Ward gave me control over my data and unlocked things I hadn't imagined: from training machine learning models that accurately predict acoustic performance to automating full workflows. A game-changer for any data-driven engineer”
“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“
“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"
Used by engineering teams at
"We generated data across seven simulation and test environments. Key Ward connects all of it automatically; structured, queryable, and ready for Al/ML with dashboards that give stakeholders instant visibility. Groundbreaking for any data-drive engineering team. We are already seeing fruits and can't wait until we are fully migrated with all our data in one place!"
”Key Ward helped FEV turn simulation data into reusable engineering intelligence that enabled faster convergence, lower cost experimentation, and scalable CFD workflows.”
“Key Ward reduced RFQ time from 1.5 months to days. And it’s got a great interface as well.”
“The missing link between your data and your reporting. Key Ward gave me control over my data and unlocked things I hadn't imagined: from training machine learning models that accurately predict acoustic performance to automating full workflows. A game-changer for any data-driven engineer”
“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“
“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"
Used by engineering teams at
/ problem
95% of Engineering AI Initiatives Fail to Scale from Pilot to Production
The problem isn’t the AI model. It’s the missing data infrastructure.
Key Ward is the infrastructure that puts you into the 5%
3D meshes
Multi-physics
solver specific, not compatible for modern AI
1D signals
CSV
HDF5
SQL
Process Logs
Quality Data
Time-Series
IoT Streams
Fragmented Workflows
Fragmented Engineering and ML Stack
Outcome
Reproducible 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
/ roi calculator
Every week your engineers prepare data instead of analysing it. That is money you are not getting back.
See exactly how much in under 30 seconds.
/ tell us about your team
How much is your engineering team losing to manual data prep?
See how much time your team loses to manual data prep, and what it actually costs your business, in under 30 seconds.
In under 30 seconds, you’ll see:
Your current annual cost
Estimated savings with Key Ward
Estimated engineering hours per month
Time to see full ROI
Total cost of ownership (if done internally)
How big is your engineering team?
Include simulation, test, CAE, or manufacturing engineers who work with data
25
Small (5)
Mid-size (25)
Large (60)
Programme (120)
How many times per week does an engineer manually collect, clean or format data?
Think of one engineer, how often do they move files, reformat outputs, or pull data from different tools before starting analysis?
3X/week
Rarely (1X)
Often (3X)
Daily (5X)
Multiple daily (8X)
What is your average hourly cost per engineer?
Salary + benefits + overhead. No need for an exact number. Most senior engineers in automotive and aerospace cost $70–$120/hr fully loaded.
$85
Junior ($60)
Mid ($85)
Senior ($110)
Principal ($150)
< go Back
Your annual real cost of fragmented engineering data
$1,480,020
That is how much a 25-person team doing data prep 3× per week at $85/hr is losing every year to work that Key Ward automates
Spend up to 4X* less on manual data preparation
*Based on deployments at FEV (70% DoE reduction), Carnot (manual post-processing eliminated), and others, 75% is a conservative estimate.
Estimated annual cost of data preparation with Key Ward
Your current annual cost of data preparation
Total savings with Key Ward
$1,480,020
Engineering hours per month
1,451 hours
Without Key Ward
363 hours
With Key Ward
Mid-size engineering teams like yours typically see full ROI within 4–6 months
Why not build it yourself?
Building equivalent infrastructure in-house costs ~$590K/year in engineering headcount, data systems, and maintenance. Key Ward gives you all of that without the build cost, the headcount, or the maintenance overhead.
/ Get your report
Get your full engineering ROI breakdown
A complete breakdown of your cost, time loss, ROI timeline, and workflow improvements, ready to take into your internal discussion.
/ 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.
A Tier 1 Supplier Reduces Scrap and Improves 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.
An 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
Concept
“The missing link between your data and your reporting. Key Ward gave me control over my data and unlocked things I hadn't imagined: from training machine learning models that accurately predict acoustic performance to automating full workflows. A game-changer for any data-driven engineer”
Validation
"We generated data across seven simulation and test environments. Key Ward connects all of it automatically; structured, queryable, and ready for Al/ML with dashboards that give stakeholders instant visibility. Groundbreaking for any data-drive engineering team. We are already seeing fruits and can't wait until we are fully migrated with all our data in one place!"
Dr. Jeremy Howard-Knight
Head of Business Development
Modeling
”Key Ward helped FEV turn simulation data into reusable engineering intelligence that enabled faster convergence, lower cost experimentation, and scalable CFD workflows.”
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"
/ 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.
