Engineering Answers, Not Black Boxes
A software kit that replaces slow simulations with fast, uncertainty-aware predictions — often in seconds.
It combines our unique probabilistic modeling, Bayesian optimization, and generative AI in a single platform built for engineering workflows.
STOCHOS is a complete machine learning toolkit for physical modeling, optimization, and generative design in engineering. It allows users to train high-accuracy surrogate models with minimal data, predict fields, signals, and complex geometries in seconds, and quantify uncertainty for trustworthy, engineering-grade results. STOCHOS supports both parameter optimization and full design optimization through Bayesian methods, automatically generates new geometries with generative AI, and enables the creation of agentic AI workflows that automate entire engineering processes. At its core, STOCHOS is powered by our unique DIM-GP algorithm — a deep infinite mixture of Gaussian processes capable of handling changing geometries, meshes, noise, multi-fidelity data, and physics-consistent behavior, all without the need for manual tuning.
high-accuracy engineering predictions –
fast, reliable, and built for real-world complexity.
A Distinctive AI Technology for Real-World Engineering
Our self-developed AI technology is a globally unique approach to engineering intelligence. Built specifically for physical data, it combines advanced probabilistic modeling with precise noise recognition to deliver reliable, transparent predictions — even when only limited data is available. Unlike conventional black-box ML models, our method provides a confidence measure for every single output, allowing engineers to immediately see where the model is certain and where further data would strengthen the result.
Pin Fin Cooling:
STOCHOS predicts correctly temperature and heat flux in <5 secs. for a new design
CFD example: water around a cylinder
9.867 training steps, 1 epoch = 5 samples, 5 min. on GPU.
PI-BO Bayesian Opimization
Our platform includes advanced Bayesian optimization methods that automate the search for optimal parameters or complete designs using only a minimal number of samples. The algorithms balance exploration and exploitation in a principled way and support both multi-objective and multi-fidelity optimization tasks, integrating directly with existing simulation environments or laboratory workflows. This provides a systematic and data-efficient approach to navigating high-dimensional design spaces, reducing the need for exhaustive simulations or experiments while ensuring that engineering constraints and real-world considerations are rigorously accounted for.
Example: minimize vertical displacement (mm), 5 Startdesigns, best result 0.238mm after 50 designs, optimization <10min
Generative AI for Geometry Creation
Generative AI enables the creation and exploration of complex design spaces by learning the underlying structure and constraints of existing geometries. From only a few representative examples, it can produce large sets of plausible variations that adhere to functional and geometric requirements. This allows engineers to investigate alternative shapes, evaluate different design directions, and identify novel solutions that would be difficult or time-consuming to derive manually. By generating and comparing many valid candidates in a short time, generative AI supports a more systematic and efficient development process and opens up new possibilities for design innovation.
Agentic AI for Engineering Workflows
If most of your time goes into automating workflows, connecting tools, and writing custom scripts instead of engineering itself, this is for you.
We’re proud to introduce Stochos Flow — a visual workflow editor that brings the full power of Stochos into an intuitive, AI-driven environment. Built by engineers, for engineers.
Stochos Flow lets you describe what you want to build, and the agent does the work alongside you. It creates nodes, wires workflows, configures parameters, and helps debug directly on the canvas—so you can build AI models, run optimizations, generate data, connect simulation tools, and write custom scripts without friction.
Everything runs 100% locally. No cloud, no data leakage, no IP risk—designed for real engineering environments.
Stochos Flow is powered by RAG-based engineering knowledge, allowing you to teach the agent your internal standards, proprietary methods, solver APIs, and workflow documentation. Your knowledge becomes instantly accessible and actionable.
Built to extend—not constrain—Stochos Flow supports custom Python solver nodes, tool integrations via MCP servers, one-click export to web apps, and workflow export as standalone, production-ready Python code. Your workflows are never locked in.
The result: less infrastructure work, fewer brittle scripts, faster iteration, and more time focused on solving real problems.
Stochos Flow is where AI meets engineering intelligence.
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