Classical algorithms
Solve problems on today’s hardware that established methods cannot reach.
We solve quantum problems. The right answer might be a classical algorithm today, an AI model trained on better data, or a quantum algorithm running on fault-tolerant hardware tomorrow.
01 · Who we are
Quantum problems do not care which machine solves them. Neither do we. Our physicists and data engineers develop new algorithms when established methods stop working.
Solve problems on today’s hardware that established methods cannot reach.
Train models on reliable physical data instead of sparse, inconsistent datasets.
Quantum circuits for fault-tolerant systems of the future.
02 · What we do
Machine learning can search materials space at extraordinary speed, but the data available to train and validate those models is often too sparse, inconsistent, or unreliable.
We are building the engines that produce accurate physical data at the speed and scale modern discovery programs require.
Physics-based calculations.
Reliable data at useful scale.
Train and validate on stronger evidence.
Discover and validate materials.
03 · How we do it
Quatrain is our first engine, built for quantum calculations that become impractical with established methods.
Where established methods break down
More tractable scaling. Greater throughput. High-accuracy calculations for larger quantum systems at finite temperature.
01 · Electronic orbitals
1000s
Solve larger molecular systems.
02 · Finite-temperature calculations
298 K
Capture finite-temperature effects at room temperature.
03 · Computational scaling
State of the art
Generate more high-quality data in less time.
Every engine we develop follows the same logic: find the computational barrier, build the right algorithm, and turn previously unreachable calculations into usable scientific capability.
Classical algorithms, AI models, and quantum algorithms in one computational toolbox.
Work with us