Predict and forecast likely future outcomes across the business cycles using machine learning to find correlations to identify patterns within the data. Our data scientists design models that work across various production cycles, management, marketing, and operations, with seamless integration.Predicting patterns eventually reduces time, effort, and costs in forecasting business outcomes.
Classification and categorization
Sentiment and behavior analysis
We get down to business the minute we get what exactly you need. The problem statement is the first step we take very seriously until the end. We practice asking very specific questions to the point of not missing even the minutest detail.
Data collection is a sticky area where we cannot predict which speck of data might come in handy. On the other hand, collecting everything and anything for a project might prove counter-productive. Our data scientists workbackward to take every stakeholder and the KPIs into consideration to extract the correct data in the proper format and the right frequency.
Data cleansing is the most crucial part of a data science project. It entails dealing with inconsistencies, identifying problematic errors that clearly demand a data development plan in advance, and revising it regularly in case of big data. It is the most grueling phase, which needs manpower and time to derive clean data. We use advanced AI tools which are affordable and effective to meet your requirement in the expected time.
Understanding the business is crucial to arrive at a model that clients understand find worth considering for business development. Arriving at such insights needs a deep understanding of business. Our data scientists leave no stone unturned to get to the nitty-gritty of your business, and the entities required.
Model Deployment needs as much thought process as for model development. Deployment requires the application of a model for prediction using new data. You need to understand how the end-user will interact with the model's prediction. At RVG, we ensure that we keep the deployment pipeline flexible and organic so that our clients can test it repeatedly.
Data science and AI are few among the latest technologies which can prove revolutionary in medical science. Helping reduce errors in diagnosis, treatment, and preventive medicine is one of the defining technologies in the medical field.
E-commerce is one field that generates data more than any other sector. It would be only unwise for E-commerce portals not to leverage the humongous data present on the web. From buyer behavior, inventory management to forecasts on value prediction of a buyer, there is no area in which data science cannot help the E-commerce industry.
Finance and banking
When objectivity is the goal, data-driven decisions only can help you achieve one. The finance and banking industry realizes this fact quickly and adapts to it in customer data management, fraud detection, credit and investment risk modeling, and customer segmentation.
Precise methods and platforms available in data science help predict demands and curate course content accordingly. We design models to assess teacher and student performance based on critical parameters to arrive at the closest evaluation.
With that being said, the good news is that Reliant Vision has the required tech expertise in understanding the business processes of clients from across industry verticals and we come up with the right solution for them.