SciLM.ai
SciLM SubsurfaceGive it the field's data. Get every geology that fits.SciLM Atomic StructureGive it what you measured. Get the atomic structure back.SciLM Atomic KineticsGive it a material. Get its kinetics back.DataTwo open datasets, and data generated to order.
SciLM SubsurfaceGive it the field's data. Get every geology that fits.SciLM Atomic StructureGive it what you measured. Get the atomic structure back.SciLM Atomic KineticsGive it a material. Get its kinetics back.DataDatasets, engines, models, data to orderThesisWhy science needs a model that seesRoadmapData first, models now, SciLM nextTeamThe founders and the advisors

Data

More than every laboratory in history has measured.

Generated by physics-based simulation, with the domain expertise of geoscientists, physicists, chemists and engineers built in. The first datasets are open, under CC-BY 4.0, with the engines that made them. The next will be licensed, or generated to your specification.

Released so far.

MaterialsSaddles

Reactant, transition state and product for reactions across inorganic materials.

34.14 Mreactions
102.4 Mstructures
687 GBCC-BY 4.0
DatasetSaddleMill, the engineSaddleFlow, the model

SiliciclasticReservoirs

Synthetic 3D oil and gas reservoirs across eight depositional architectures, with facies, porosity and permeability per voxel.

1,000,000reservoirs
8architectures
787 GBCC-BY 4.0
DatasetResMill, the engineResFlow, the model

Data to order.

The engines that generated a million reservoirs and 34 million barrier crossings run for you: your system, your scale, your sampling, in the form your models read. Exclusive or non-exclusive licenses, for the subsurface and for materials alike.

The engines

  • SaddleMill (MIT): high-throughput transition-state generation across inorganic materials.
  • ResMill (MIT): rule-based 3D reservoir modeling, eight depositional architectures.
  • PotMill (BSD-3): an ML interatomic potential from data generation to the final model in under one day.

The models

  • SaddleFlow: the first generative model for transition states in inorganic materials; behind SciLM Atomic Kinetics.
  • ResFlow: one model for every siliciclastic reservoir type, any wells, any field size; behind SciLM Subsurface.
  • Both papers are under review at NeurIPS 2026.
Order dataHugging FaceGitHub

If the data or model you need does not exist yet, write to us.

We generate simulation data and train AI models to specification: the physics, the systems, the sampling and the format, for the subsurface and for materials alike. Exclusive or non-exclusive licenses.

  • Datasets: MaterialsSaddles and SiliciclasticReservoirs are open; the next are licensed.
  • Models: ResFlow and SaddleFlow, licensed as tools or trained on your data.
  • Data to order: your system, your scale, in the form your models read.
[email protected][email protected]
GitHubHugging Face
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