We support R&D teams facing complex analytical or computational challenges, delivering models, algorithms, and methods designed for accuracy and robustness under real‑world constraints.
Areas of expertise
Physical system modeling
We develop analytical and numerical models of mechanical, acoustic, and multi‑physics systems to guide design decisions, predict performance and validate concepts.
Our work supports applications such as precision watch components, acoustic detection systems, advanced sensing architectures and other complex dynamical mechanisms.
Machine learning and data-driven analysis
We build forecasting, classification and decision‑support methods that remain robust under operational conditions.
Our experience includes demand prediction, particle characterization, anomaly detection and probabilistic modeling for high‑stakes decision processes.
Quantum technologies
We assist teams exploring quantum computation and communication by providing algorithmic expertise, hardware‑level insight, and architectural modeling.
Our work spans algorithm execution on quantum hardware, network‑level analysis and computational methods for emerging quantum architectures.
Selected results
A selection of public outcomes from significant work, illustrating the range of technical projects addressed:
- Balance spring for a timepiece resonator. We design balance‑spring geometries with tuned thickness and pitch profiles to reduce rate variations.
- Transient acoustic detection for hostile‑fire indication. We develop signal‑processing methods to detect short‑lived acoustic events under challenging conditions.
- Differentiating and quantifying non‑exhaust particles in traffic road dust. We integrate SEM/EDX analysis with automated classification to conduct source apportionment.
- Prediction of outcomes in Swiss popular votes. We integrate media, party and polling signals into machine‑learning models to predict collective decision outcomes.
- Analog counterdiabatic quantum computing. We build computational and control techniques that advance the capabilities of analog quantum devices.
About us
At Gradiom, we work with organisations across research and industry, often under strict confidentiality. While only part of our work can be shared publicly, selected publications offer a glimpse of our methods and technical standards. Our work combines analytical precision with pragmatic implementation, ensuring that models and methods remain usable in real operational settings. We welcome conversations with teams exploring new challenges. You can reach us directly via LinkedIn for inquiries or initial discussions.