Building an enterprise-grade AI model is highly dependent on the amount of data that one can gather for training models. We develop tools and frameworks to source data from the open web that is later converted into training data. We also partner with large enterprises and help them prepare data for the purpose of model development. We follow strict standards around confidentiality and use to protect proprietary data from our partners.
The data required to build enterprise-grade AI models are significantly larger than most people expect. We are building on top of the data sets collected by cities over the past several years to meet the growing demand for AI models in the industry.
Generating training data is one thing; actually training a model on an enormous amount of city, county and state data presents its own set of challenges. We spend our engineering prowess to build out a robust distributed training systems to handle models with training datasets that have more than several hundred million items.
Even after a model has been trained, deploying the model to handle a production-level load, capable of processing billions of API requests per month across various GPU clusters in our data centers today.
We embed our AI models in stand-alone applications that allow any business user to leverage the power of artificial intelligence. We are developing a sophisticated urban analytics suite for city planners, real estate investors, and property owners
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