Dataeaze systems is focused on making it easy for organisations to work with data. We help organisations build "data driven" software products, by incorporating domain knowledge and leveraging machine learning. With artificial intelligence and deep learning techniques, we build "software 2.0" data pipelines for all kinds of data -- streaming or big data, structured or unstructured.
Emergent technologies in fiber optics have brought in a new set of engineering problems that demand for artificial intelligence/machine learning approaches. Dataeaze helped us to tap the power of computer vision and deep learning techniques for the modeling of one such engineering problem. Following a rigorous data science and engineering discipline, they built a software stack for us. It was a complete ''software 2.0'' lifecycle execution, from ideas in the research lab to the code deployable in production. I wish them success and hope to work with them again in the future.
I had the pleasure of working with Dataeaze over the course of a year - their passion for AI, deep technical expertise and focus on execution helped us to build a complex deep learning solution from ideation to deployment in 8 months. They take full ownership of the pipeline and understand the complexities of production. Ajit is a mature leader of his team and this shows in their ability to retain world-class talent.
The product was delivered within a reasonable time. The Dataeaze team proved to be flexible when faced with challenges and project unknowns, coming up with solutions and new ideas. They reported on a weekly basis and used a transparent project management style.
Clients and Partners
How do we help?
End to end data lake bringup and maintenance
Bring up an enterprise grade robust and scalable hadoop big data lake and reporting data mart Suitable to your use cases and data scale needs. Resolve source data complexity and bring your existing data on board maintain this platform to make sure use cases are served on time
Implement data engineering automation
Setup automated data ingestion pipeline. Design and build reporting data mart. Build ETL workflows as per analytics requirements
Implement data analytics use cases
Analyse your data, your use case needs Architect, Implement end to end ETL + interactive data store load + API layer Make MIS reporting, Machine Learning and Real Time reporting possible on this platform