We can get you going quickly, without having to scrub years of experimental data. From the first day you log in to putting AI in the hands of every technical mind at your company, we’ll help you every step of the way. At a high level, you’ll start by choosing the project, preparing your data, and building your AI models. We’ve successfully completed a large number of AI adoption projects across a wide range of industries, and our team will help you identify and scope high-value projects that are likely to bring you real value, right from the start. Every company’s needs are unique, and we’ve built an adoption process that is highly flexible. Building your internal capabilities We give your team the training they need: - Flexible, customizable training content presented to your Working Team by Citrine’s Materials Informatics experts - Course syllabus structured into multiple short engagements, designed to keep your team engaged - Targeted training to educate your R&D scientists, project leaders, and IT professionals, laying the groundwork for new technology adoption - “Train the trainer” process to quickly establish in-house expertise Finding your high-value projects, preparing your data Our adoption specialists help you arrange a meaningful proof-of-concept: - Structured process with your working team to identify and scope suitable first projects - Identify associated data sets and data streams - Create a data structure relevant to your company’s unique materials profile - Transfer data to our operating platform using Citrine DataManager Creating, refining, and validating your initial models After your project data is digitized and searchable, we work together with you to build the first AI model: - Generating a first-pass model based on training data - Refining your model using your team’s specific domain knowledge - Using your model’s results in Citrine VirtualLab to suggest which candidate materials should be synthesized and tested - Validating your model’s accuracy - Iterate, by feeding data from select experiments back into the platform and re-running the model with more data Developing the broader roll-out plan Once you’re comfortable with how the platform operates, you’ll lead the next adoption phase, with our team standing by to provide additional support as needed: - Helping you develop a training and deployment plan to expand access to the platform - Identifying the most likely areas to benefit as part of the business case - Providing ad hoc professional support to supplement your own teams’ data science capabilities, if needed
