Building Reusable Engineering Intelligence for Industry Leaders
Key Ward enables industries built on multi-system simulation, testing, and design programs to move from fragmented data and one-off analyses to reusable engineering intelligence.
By connecting multi-source engineering systems into a unified environment, teams can access, analyze, and reuse data to build automated workflows and machine learning models that improve over time.
Automotive & Mobility
OEMs and suppliers gain a competitive edge by accelerating engineering cycles and reducing reliance on costly simulation loops.
Screen design candidates without running full simulation workflows, predict key performance metrics instantly using trained models, reduce reliance on time-intensive and expensive simulation loops
60%
faster time to insight vs. manual data preparation workflows
90%
reduction in simulation and compute costs
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Autoneum reached optimal acoustic performance for an advanced material using structured data and a repeatable workflow
Aerospace & Aviation
Aerospace engineering generates massive volumes of simulation and test data across aerodynamics, structures, and thermal systems.
Unify simulation and test datasets across programs, compare design variants and performance metrics and automate validation workflows across experiments
Thousands
of dollars saved per design iteration, resulting in multi-million-dollar savings per program
90%
reduction in simulation and compute costs
Beyond Aero Accelerates Aerodynamic Design for Next-Generation Aircraft
Industrial & Advanced Manufacturing
Industrial manufacturing generates large volumes of production, sensor, and quality data across lines and facilities.
Automate ingestion and structuring of production data, instantly visualize KPIs and correlate process parameters and save machine time with near real-time root cause analysis and failure detection
Thousands
of dollars saved per design iteration, resulting in multi-million-dollar savings per program
$230K+
in annual savings vs. repetitive manual processing tasks
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A Tier 1 Supplier Reduces Scrap and Improves Manufacturing Quality with Data-Driven Production Analytics
Additive Manufacturing
Additive manufacturing workflows require coordination across design, process simulation, and physical validation.
€0.5M
saved in scrap, energy and inefficiency
70%
faster RFQ resolution versus traditional engineering workflows
A Leading Global Industrial Manufacturer Accelerates HVAC Filter Design with AI-Driven Surrogate Modeling
Renewable Energy
Renewable energy systems generate large datasets across simulations, field data, and operational monitoring.
Integrate simulation and operational datasets, analyze performance across turbine or system variants, build predictive models for system optimization
70%
faster RFQ resolution versus traditional engineering workflows
4–5
hours saved per cycle vs. manual data handling
Beyond Aero Accelerates Aerodynamic Design for Next-Generation Aircraft
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"
