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Most chemical companies want to use AI. Very few know where to start. That’s exactly the gap Chemcopilot.com was built to close. Chemcopilot is not a generic AI tool adapted to chemistry. It is an AI-native platform designed specifically for chemical R&D, formulation, and sustainability teams. What makes it different? Built for chemical data Formulations, experimental results, BoMs, regulatory constraints, CO₂ data, tox parameters — Chemcopilot works with the data chemists actually generate. From raw data to decisions We help teams move from scattered spreadsheets and lab reports to structured data that can be used for: Design of Experiments (DoE) Predictive models (toxicity, performance, shelf life) Optimization of formulations and processes AI beyond LLMs Text models are useful, but chemistry requires more: Statistical models ML for structured experimental data Domain-specific constraints (regulatory, safety, sustainability) Sustainability by design Chemcopilot integrates CO₂ footprint logic and regulatory parameters directly into R&D workflows — not as an afterthought. In short: 👉 Chemcopilot helps chemical teams turn AI from a strategic intention into real, applied value in R&D. If your leadership asked you to “evaluate AI for chemistry”, this is the kind of conversation we should be having.