Simple solutions are often the best. Simple models are easily understood. Complex models often only exist for complexity's sake. At i2π we use the principles of basic fundamental science to build models for your business. A simple model allows the analyst and your team to consider the entirety of the model and its relation to reality at once. A complex model leaves the analyst considering complexity and not solutions.
Simple solutions are never shallow solutions. Representative analysis requires a deep understanding of all available techniques. Simplicity can be found in statistics, machine learning, computational micro-economics, graph theory and a slew of other sciences.
Only by compiling all relevant data and investigating a wide range of techniques can the best solution be uncovered. Proceeding directly to a simple end goal without this in-depth exploration results in models that fail to accurately reflect reality.
At i2π, scalability takes two forms: scalability for our clients and scalability for our business. Our background in computational analysis and optimization has taught us respect for our tools, which can process billions of calculations per second. We ensure that we are never the bottleneck as your company and data processing needs grow by teaching your company to develop its own analytic strengths, instead of simply providing insight on demand.