車の製品開発を
短期間で実現

最先端の機械学習を応用し複雑な技術課題を理解しやすくし、
開発スピードを向上させます。

車の製品開発を
短期間で実現

最先端の機械学習を応用し複雑な技術課題を理解しやすくし、
開発スピードを向上させます。

車の製品開発を
短期間で実現

最先端の機械学習を応用し複雑な技術課題を理解しやすくし、
開発スピードを向上させます。

車の製品開発を
短期間で実現

最先端の機械学習を応用し複雑な技術課題を理解しやすくし、
開発スピードを向上させます。

Secondmindアクティブラーニングを使用することで、データに基づいて自動で成立する設計仕様を見つけることが可能になります。多次元の設計空間を可視化し、探索して、設計の早い段階で革新的な設計を特定することができたり、後工程からの手戻りを削減し、時間を節約します。

Request demo

メリット

開発時間を半分にし、システム設計のためのSecondmindを使用して、シミュレーションを最大80%削減します。

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.

メリット

開発時間を半分にし、システム設計のためのSecondmindを使用して、シミュレーションを最大80%削減します。

Explore more, in far less time

Map the entire feasible space with up to 90% fewer simulations a fixed plan would need - surfacing high-performing designs previously out of reach.

Commit with confidence

Carry multiple feasible designs forward, and commit only once confidence is high enough to get it right, first time - avoiding costly late-stage rework.

Visible trade-offs, room to adapt

See exactly where the best trade-offs lie, and when a requirement changes, its impact is visible immediately - without restarting from scratch.

Explore more, in far less time

Map the entire feasible space with up to 90% fewer simulations a fixed plan would need — surfacing high-performing designs previously out of reach.

Commit with confidence

Carry multiple feasible designs forward, and commit only once confidence is high enough to get it right, first time — avoiding costly late-stage rework.

Visible trade-offs, room to adapt

See exactly where the best trade-offs lie, and when a requirement changes, its impact is visible immediately — without restarting from scratch.

メリット

開発時間を半分にし、システム設計のためのSecondmindを使用して、シミュレーションを最大80%削減します。

Explore more, in far less time

Map the entire feasible space with up to 90% fewer simulations a fixed plan would need - surfacing high-performing designs previously out of reach.

Commit with confidence

Carry multiple feasible designs forward, and commit only once confidence is high enough to get it right, first time - avoiding costly late-stage rework.

Visible trade-offs, room to adapt

See exactly where the best trade-offs lie, and when a requirement changes, its impact is visible immediately - without restarting from scratch.

Explore more, in far less time

Map the entire feasible space with up to 90% fewer simulations a fixed plan would need — surfacing high-performing designs previously out of reach.

Commit with confidence

Carry multiple feasible designs forward, and commit only once confidence is high enough to get it right, first time — avoiding costly late-stage rework.

Visible trade-offs, room to adapt

See exactly where the best trade-offs lie, and when a requirement changes, its impact is visible immediately — without restarting from scratch.

Explore

主要な機能

Secondmind gives engineers different features to map the design space, compare candidates, and commit with confidence.

Secondmind gives engineers different features to map the design space, compare candidates,
and commit with confidence.

成立設計仕様

要件を満たすことが検証された設計仕様を開発初期段階に選ぶことで、コストのかかり開発手戻りを防ぎます。高額なやり直しのリスクを排除します。

成立する設計仕様を指導的に見つけ出す。

要件が成立する設計仕様を開発検討チームに渡してください。

設計の修正・手戻りを最小限に抑え、時間とコストを抑えます

最先端の可視化

直感的な可視化により、データが持つ重要な意味をを理解してください。

複雑で多次元の設計空間だとしても、安心して探索してください。

設計値でのスライス、設計空間の2D投影、パラレルコーディネート図など、さまざまな手法でデータを可視化します。

効率的にトレードオフを分析して、最適な解決策をより早く選択します。

最先端の可視化

直感的な可視化により、データが持つ重要な意味をを理解してください。

複雑で多次元の設計空間だとしても、安心して探索してください。

設計値でのスライス、設計空間の2D投影、パラレルコーディネート図など、さまざまな手法でデータを可視化します。

効率的にトレードオフを分析して、最適な解決策をより早く選択します。

誘導案内付きの設計仕様の探索

当社の先進的な分析力を得て、勘と経験だけに頼らない意思決定をしましょう。

利用可能な設計仕様の選択肢を網羅的に調査できます。

実現可能性の限界を理解して、革新的な解決策を特定します。

要求性能を満たす設計領域を可視化することで、要求性能のしきい値変更が設計仕様に与える影響を理解することができます。

誘導案内付きの設計仕様の探索

当社の先進的な分析力を得て、勘と経験だけに頼らない意思決定をしましょう。

利用可能な設計仕様の選択肢を網羅的に調査できます。

実現可能性の限界を理解して、革新的な解決策を特定します。

要求性能を満たす設計領域を可視化することで、要求性能のしきい値変更が設計仕様に与える影響を理解することができます。

誘導案内付きの設計仕様の探索

当社の先進的な分析力を得て、勘と経験だけに頼らない意思決定をしましょう。

利用可能な設計仕様の選択肢を網羅的に調査できます。

実現可能性の限界を理解して、革新的な解決策を特定します。

要求性能を満たす設計領域を可視化することで、要求性能のしきい値変更が設計仕様に与える影響を理解することができます。

メリット

開発時間を半分にし、システム設計のためのSecondmindを使用して、シミュレーションを最大80%削減します。

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.

サステナビリティの追求

私たちは、CO2排出量を減らし、環境に優しい影響を与えることを目指しています。そのために、効率的な車両開発を通じて、自動車のネットゼロに向けた未来へのシフトを加速させたいと考えています。

Learn more

Example use cases

Complex products, dozens of interacting variables, measurable impact.

E-motor design

Reduced bill-of-materials cost by $27/unit while improving torque, reliability, and NVH simultaneously.

Piston bowl design

Explored 3x more feasible designs than existing CAE tools, in 50% less time - balancing fuel, emissions, and heat transfer targets.

3-cylinder engine design

Found a robust engine mount design in 400 simulations vs. 78,000+ conventionally required - uncovering a hidden interaction standard methods missed.

Example use cases

Complex products, dozens of interacting variables, measurable impact.

E-motor design

Reduced bill-of-materials cost by $27/unit while improving torque, reliability, and NVH simultaneously.

Piston bowl design

Explored 3x more feasible designs than existing CAE tools, in 50% less time - balancing fuel, emissions, and heat transfer targets.

3-cylinder engine design

Found a robust engine mount design in 400 simulations vs. 78,000+ conventionally required - uncovering a hidden interaction standard methods missed.

Learn more

サステナビリティの追求

Learn more

サステナビリティの追求

Example use cases

Complex products, dozens of interacting variables, measurable impact.

E-motor design

Reduced bill-of-materials cost for a major OEM by $27/unit while improving torque, reliability, and NVH simultaneously.

Piston bowl design

Explored 3x more feasible designs than existing CAE tools, in 50% less time — balancing fuel, emissions, and heat transfer targets.

3-cylinder engine design

Found a robust engine mount design in 400 simulations vs. 78,000+ conventionally required — uncovering a hidden interaction standard methods missed.

Example use cases

Complex products, dozens of interacting variables, measurable impact.

E-motor design

Reduced bill-of-materials cost for a major OEM by $27/unit while improving torque, reliability, and NVH simultaneously.

Piston bowl design

Explored 3x more feasible designs than existing CAE tools, in 50% less time — balancing fuel, emissions, and heat transfer targets.

3-cylinder engine design

Found a robust engine mount design in 400 simulations vs. 78,000+ conventionally required — uncovering a hidden interaction standard methods missed.

Example use cases

Complex products, dozens of interacting variables, measurable impact.

E-motor design

Reduced bill-of-materials cost for a major OEM by $27/unit while improving torque, reliability, and NVH simultaneously.

Piston bowl design

Explored 3x more feasible designs than existing CAE tools, in 50% less time — balancing fuel, emissions, and heat transfer targets.

3-cylinder engine design

Found a robust engine mount design in 400 simulations vs. 78,000+ conventionally required — uncovering a hidden interaction standard methods missed.

Learn more

サステナビリティの追求

Learn more

サステナビリティの追求

Learn more

サステナビリティの追求

Learn more

サステナビリティの追求

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サステナビリティの追求

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