Using AI-first approach our experienced data science and development teams teams will coordinate with you to build optimal solutions that will fulfil your requirements and also provide flexibility for future evolution, thereby guaranteeing reliability and maintainability.
We have an impressive track record of having delivered AI solutions across multiple domains. With Drive Analytics, you can be assured of superior outcomes, transparency, minimized pain points and a well structured delivery methodology. You can check analytics off your to-do list with best practices baked right in!
We sit together with the client and define the problem to be solved and set the goals of the project along with the timelines and roles and responsibilities etc.
We take a deep look at the data sources available, and explore the options for augmenting the data through various means. We also define the data pipeline which includes taking the data from its raw source to a format that can be taken up for model training.
Raw Data in its whole can be quite overwhelming to handle. We look for the most relevant features of the data by leveraging domain knowledge and by applying analytical methodologies. We then select and transform most relevant variables from the raw data to send it up for training models
We iterate through the model development by trying out the best approaches for training. We tune the AI network layers, we tune the training hyper parameters, we try out different types of AI networks, we also ensemble models, to come up with the optimal solution for the problem.
The models are test-driven by the business team on unseen data. They are tried under various conditions to ensure that they meet the acceptance criteria. With new findings, the models go through a few more iterations of refinement before they are considered mature and stable for moving into production.
We typically host the models and serve them via APIs. The hosting is usually done on the cloud taking into account the security considerations of the client. We also put systems in place so that the health of the production system is monitored continuously and there are no glitches to the business operations.
