Secondmind for Design Space Exploration maps the entire feasible design space with minimal simulations. Engineers can focus exploration only on designs confirmed to meet requirements — surfacing novel design candidates that conventional approaches could never reach, since they are limited to a single starting point.
The challenge
Complex systems create complex trade-offs — and conventional tools aren’t built for them, slowing teams down and putting program delivery at risk.
Months spent, only a fraction of the space explored
Time pressures mean it is only possible to explore a small part of the design space — committing resources means gambling on a direction with no way to confirm it's the right one.
Costs lock in before the evidence exists
Early decisions commit most of a program's cost, before conventional tools have enough data to produce reliable evidence — so by the time a gap surfaces, it's far more expensive to fix.
No proof it's the best design — and no room to adapt
Without visibility across the full space, there's no way to confirm a better trade-off doesn't exist elsewhere — and any requirement change resets the timeline.
Requirements Visualizer
Adapt to changing requirements, instantly — no new simulations required.
Adjust a requirement threshold and see the impact on feasibility.
Identify which requirements are actually limiting the design — and relax them to open up new feasible designs.
Challenge or defend a requirement with data, not opinion.
Multi-objective Optimization
Reveal the best trade-off across multiple requirements.
Identify where the best trade-offs lie.
See how far one requirement can be pushed before conceding ground on another.
Compare trade-offs within existing constraints and requirements — not a separate, unconstrained search.
Feasibility Boundary
Know the absolute limits of what's possible.
Map the full boundary of every design that meets system-level requirements.
Confirm every viable option has been considered, with nothing feasible left undiscovered.
Present stakeholders with a clear view of what is, and isn't, possible before committing to a direction.
Safe Operating Envelope
Develop in parallel, without integration risk.
Explore a set of designs already confirmed to meet system requirements.
Work in parallel across different teams from a shared feasible design space.
Avoid downstream integration conflicts since every team is developing within a shared, compatible feasible design space.
Proven results
Delivers faster time-to-market, lower development costs, and better-performing results.
Faster
time-to-market
6x faster
Hundreds of feasible designs found in just two weeks, where incumbent tools yielded zero results after three months.
Lower
development costs
90%
reduction in CAE simulation runs compared to standalone CAE tools.
Better quality and performance
$27
per-unit BOM cost reduction
— an estimated $11M in annual savings at mass-production volumes for one OEM.
The Secondmind advantage
The technology powering the result — working together, not in isolation.
Every single simulation earns its place
Secondmind Active Learning targets the gaps in the model rather than collecting data indiscriminately — reaching a reliable result in a fraction of the simulations a fixed plan would need.
Precision where it matters — the boundary itself
Model precision concentrates around the feasibility boundary, not spread evenly across the whole space. Every result carries a confidence level, so engineers know when that boundary can be trusted.
The entire feasible space, made accessible
Rather than a single design point, engineers get a full set of viable options, faster than conventional sampling. Interactive plots reveal which parameters drive performance and where trade-offs emerge.
Enterprise-ready
ISO 27001 certified. Cloud-native, browser-based, no new infrastructure.
Integrates with existing CAE workflows, including GT-Suite, MATLAB/Simulink, and JSOL JMAG.
