AI Modeling
The current industry standard when it comes to AI is that only 10% of developed AI models are deployed. Our team has a 90%+ success rate in developing AI models which have been deployed and generated value for the companies.
Our philosophy for model development is to break down large problem statements in smaller chunks based on business intuition and start developing business relevant models in a timespan of weeks rather than months to start generating value and hence ROI for the company.
Our model development methodology constitutes frequent meetings with the business to incorporate business acumen/expertise into the model so as to deliver a product which will have high confidence of the stakeholders and will remain relevant for the company for several years.
Our model delivery philosophy is to not deliver a “black box” model. By utilizing in-house developed tools, we develop models with the capability of “business explanations” which further the confidence of stakeholders.
Descriptive Analytics
Visualizations & Dashboarding (Tableau, Power BI, DOMO, Quicksight, Looker, Spotfire, R Shiny, etc.)
Experiment Design (power analysis, etc.)
Statistical modeling (generalized linear mixed model, etc.)
Predictive modeling (traditional ML, NLP, deep learning, LLM, etc.)
Optimization modeling (constrained programming, mixed integer linear programming, scheduling, etc.)
Statistical Measurement (difference in difference approach, test/control significant test, etc.)
Simulation study