Overview
Sapphire ensures large scale deployments by supporting data management, to feature management, model training and validation to serving inferences in real time. Reduce development, maintenance and technical support requirements, Allow developers and data scientists to focus on true areas of expertise, Reduce time to deployment for models from years to 6-8 months.
Curate, process and collaborate with data stream
Sapphire’s powerful data managed architecture augments data to infocubes. Artificial Intelligence and Machine Learning algorithms runs with in intelligent and scalable framework. Smart algorithms identify keywords. NLP engine translates those keywords into human readable format. Architecture is dynamic and agile in nature.
Un-structure to Structure :
The plethora of data that companies use creates opportunities. One cannot overstate the problems it can generate if critical data is inconsistent across systems and mistreated as a result. The chances of any company suffering due to such challenges increase ten folds when data workers realize that more than 90% of the data they operate on is unstructured. Moreover, companies are under many regulatory therefore, efficient management of the massive unstructured data becomes more important.
The most efficient way to deal with such massive amounts of unstructured data is to have a strategically devised system for data management. Data collaboration platform, brings data from various sources leveraging power of ETL. Search, process and store data.
Intelligent :
Data is being sanitised and organised in meaningful into infocubes.
Secure : [ On cloud or on Premise ]
These infocubes are small, secured and scalable. Data is secured from any external threat. Encryption allows every single row of data stay secured.
Categorisation and Classification of data :
The process of dividing data into categories to be used more efficiently is known as data categorization. The classification process makes data easier to identify and retrieve at its most basic level. Data classification is critical for risk management, compliance, and data security. It entails categorizing information to make it more searchable and trackable. It also removes multiple data duplications, saving money on storage while speeding up the search process. Every infocube is prepared make to order. Algorithm, logic and coding is based on business vertical and process requirements.
Collaborative :
Infocube deployed on cloud is collaborative in nature. Tableu, Power Bi, Chatbot and RPA analysis are running on top of that. Optimised platform delivers faster results. Tablue and Power Bi helpd to draw charts and dashboard. Data landscape is being prepared and used by several tools.