Whether you're launching a big data initiative, moving to the cloud, or revamping your existing solution, we can help your company go from data to insights
Great companies understand their data within the context of their business, and they use it to deepen insights and drive smarter decision-making. Great companies turn to Clarity.
Our expertise in advanced data science consulting is combined with a proven ability to turn insights into action. We leverage innovative techniques—such as AI modeling, machine learning, robust scenario planning and predictive modeling—to understand your needs, identify risks and opportunities and recommend actions and potential outcomes. The result is reduced costs, minimized risks, optimized processes and major competitive advantages for your company.
What We Do
Models and Analytics
Automation through Machine Learning
Ideation, Innovation, Industrialization
Success in advanced analytics is about more than big data or the latest statistical technique. It's about understanding business interests and opportunities, then putting data to work to achieve them. Clarity's consultants are versed in both business and analytics and can engage experts within the business as well as domain experts in modeling disciplines leading to business results
Model Development SOP
Clarity's model development framework ensures that no stone is left unturned, creating the rigor needed to bring big ideas to production. The framework is holistic, considering all components of the business problem, from inception to implementation.
Analytics Center of Excellence
To aid the diffusion of analytics throughout the enterprise, Clarity works with clients to create an analytics Center of Excellence (CoE) using co-sourced talent models. Co-sourcing accelerates acclimation to the CoE model through Clarity knowledge sharing. Clarity uses its "Ideation, Innovation, Industrialization" framework to solve for the people, process and technology aspects of building the analytics CoE. This approach allows us to enact key processes needed for long-term success, as well as identifying quantifiable, actionable benefits to show immediate benefits of the effort.
Model governance not only ensures that new models are the best possible fit for the business, but also that they continue to deliver on their objectives once in production, with an agile pathway for continuous improvement and enhancement.
Having a model governance strategy with clear roles, ownership and processes is essential if companies are to make the most of their analytics investments. Clarity helps clients build this strategy, streamlining this multidisciplinary activity.
I built a classifier using AI and natural language processing (NLP) that was 99% accurate in detecting whether news articles were real or fake news. I obtained the articles by web scraping real and
Prinicpal Data Science Consultant Shantanu Raghav, along with Director of Data Science Gabriel Mohanna and Data Science Consultant Adam Zebrowski, break down neural networks, TensorFlow and common
The promise of advanced analytics capabilities is incredibly tantalizing, but actually reaching that level of sophistication can be an uphill battle. So much focus goes into acquiring analytics tools