01 / Dynamic development teams
Entering a safety-critical domain?
You are strong in mechanical, electronics or software development. Now your product is entering a safety-critical domain, and you need a practical way to introduce safety.
Our Safety for Dynamic Development Teams approach starts with what is critical now. We use conservative assumptions, move safety-relevant information where it is needed and progressively enrich the analysis as your system and team mature.
We have supported startups and innovation teams in building this safety foundation.
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02 / Safe AI
Putting AI into a safety-critical system?
AI is entering your product or control loop. How do you choose suitable data and architecture, measure safety-relevant performance and decide which monitors or fallbacks are needed?
Our practical Safe AI engineering approach helps develop safer architectures, measurable performance and evidence for future assessment.
Hands-on work in our Safe AI Lab supports this methodology across AI Model & Runtime Safety and Robotics & Physical AI.
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03 / EcoSafe AI Platform
Is safety engineering becoming too time-consuming, complex and fragmented?
Requirements, analyses and evidence can drift apart. Change impact becomes harder to understand, while engineering knowledge stays in individual experts’ heads.
The EcoSafe AI Platform connects safety work products, retains assumptions and rationale, supports impact analysis and highlights gaps for focused expert review. Decisions become traceable and knowledge reusable. The safety expert remains the final authority.
Internal benchmarks for selected work packages showed up to 70% time reduction compared with traditional development. This is not a customer-measured result.
Explore the EcoSafe AI Platform →
