Grow your business
exponentially with
strong data practices

7 + 1 =

Behind great AI and ML applications lie strong data infrastructures and robust models.
We help you embrace analytics through a great foundation in data practices.

The possibilities are truly endless. A business can gain a major competitive edge by predicting prices, demand and other critical growth variables efficiently. However, the enthusiasm to get these rich insights should not override the need to build strong data infrastructures. We bring all the best practices together to lay a solid foundation for data engineering, data science and data visualization.

We’ve worked on various verticals – right from healthcare, finance and telecom to supply chain, travel and manufacturing and we can help you with industry specific use cases.

What can we do?


Data engineering

We run an audit of your existing systems to find data sources – from images to sensors and documents. We process and store them with right architecture so that they can be retrieved later for insightful analytics.


Data science

Built upon sound data engineering practices are data science applications. We work on data validation and modelling to build exploratory, predictive, IPA or prescriptive analytics. Right use of AI, ML and other tech stack is our expertise.


Data visualization

We work on building industry specific dashboards and help you view data in a useful way. You can easily identify patterns and break complex datasets to take business decisions. We use Tableau, Power BI and other leading tools for rich visualization.

How we assess your level?



We investigate the data for patterns or anomalies before getting into deep analytics. The idea is to know the data in and out before concluding on a hypothesis or action.



We use real-time data as well as historical data to predict future events. It is a powerful tool to eliminate stockout situations or to build right inventory.



We use prescriptive analytics to help you evaluate the various choices available and choose the best possible outcome. It helps balance risk and rewards.



Interpretative phenomenological analysis is linked to psychology in a way and we use it to predict how a specific entity will react to a certain stimulus in a certain context.

Challenges & Solutions

Use large chunks
of unstructured
data to build
models upon

Sparity has expertise in transforming contracts, images, medical scans and other such data into structured XML to ensure an enterprise wide data integration and analytics.

Use AL & ML with
high level of

The output is usually only as good as the input. We work hard to build a strong data infrastructure with correct labelling to ensure reliability of all statistical modelling.

To augment data
without losing its

New data gets added on real-time basis and we ensure that everything is validated, cleaned and integrated in an accurate way. Even at granular level, it is sacrosanct.

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Target skillset/Offerings

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