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.
The process:
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.
Why this matters to our customers:
We have designed Citrine’s VirtualLab, DataManager, and ExpertFinder to apply cutting-edge machine learning techniques to the materials and chemicals domain. With the Citrine Platform, you are always in control. Our approach to AI is to make it as easy as possible to develop and review proposed solutions, so your teams can focus on finding results that work for your business.
New Ways of Thinking About Product Development
Generative AI isn’t magic, but it does let scientists think differently about what’s possible. We’re eager to show you how to find latent connections and alternatives that have been hiding in your data – and how to explore what this could mean across your organization.
Enabling Your Customers’ Success
The more quickly you can ramp up with the Citrine Platform, the faster you can provide solutions to the tough problems you’re solving for your customers.
Faster Adoption → Faster Return on R&D Investments
The R&D cycle at most materials companies can be frustratingly and expensively long. We can get you moving quickly, so you can start to see direct applications that have a real-world impact on your revenue.
Experience With Companies Like Yours
Each industry has distinct inputs and formulations. Each company has its own unique capabilities and research legacy. Regulations and supply chain challenges often vary by geography. Profile chemical issues in every organization vary. And odds are, we’ve seen it before. With dozens of deployments in organizations large and small and running the gamut of industries, we can help you make AI work for your team.
We succeed when you succeed. Our aim is to get you running quickly on the platform so you can get the most business value from the technology on an ongoing basis.”
Scott Carlyle
Chief Commercial Officer
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
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