Simulation Platform and Electronic Laboratory Notebook for Synthetic Chemistry paired with Quantum Mechanics and Machine Learning

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Advanced e-Notebook for Synthetic Chemistry Fully Loaded with the State-of-the-art

Ai.Kimia is an advanced chemical simulation platform and electronic notebook designed for advanced business and scientific analysis all rolled into one.

  • Built by synthetic chemists for synthetic chemistry

  • Fully integrated with quantum chemistry prediction tools

  • Data stored and ready for machine learning applications

  • Built for teams with access controls and performance analytics

Predict reaction efficacy and mechanism with
pure physics and leave rules-based informatics behind

Our core ReaQt technology allows the prediction of reaction thermodynamics and rates with pure quantum physics. Do you need to optimize reaction conditions, are you looking to build a homologous library using a synthon, do you need to improve catalytic efficiency or understand the development of a side product? ReaQt can do all this for you before you start your first experiment.

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Fully scalable on cloud resources - never wait in a queue again

Deploy thousands of reaction computations in minutes with success rates of >98%. Access millions of pre-computed molecules to lower costs and increase speed of further calculations. Scale to hundreds of core and achieve 500 reactions per minutes. Input by curl, post using our JSON-RPC API and obtain results via JSON format for facile integration into existing workflows.

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Contact ChemAlive about Ai.Qimia

For more details, trial licenses, pilot project, feature upgrades please get in touch

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ELN with Unique Focus on Synthetic Chemistry


Advanced interactive display of molecular energy and structure with manipulable 3D rendering


Build multiple libraries to organize your projects into chemical categories and specific libraries


Input list of SMILES with copy/paste or draw molecules individually in a stylish interface


Select enumeration level, routines and navigate nested data