microsoft azure services

Utilize Microsoft Azure's open & flexible cloud computing platform to make your business more efficient, reduce costs, & realize cost savings.

We help Organizations to Build, run & manage applications across multiple clouds, on-premises & at the edge, with the tools and frameworks of your choice.

Azure Solutions that are specifically curated to meet your business requirements.

Achieve incredible heights with contemporary Azure Services.

Automate > Innovate > Accelerate

Reimagine AI with one of the world’s most power digital solutions

You can easily tackle your business challenges with an Azure solution that brings together all the products, services, and third-party applications you need. No matter what your needs are, we have a solution that will work with your existing investments, from DevOps to business analytics to the Internet of Things.

Support your data processing and cloud methodologies with AI implementations.

With our digital accelerators, our customers accelerate the full life cycle of data management, data ingestion and data quality, and improve time to deliver value-added analytics services.

Data Architecture Services

We design data cloud solutions and also prepare and automate ETL processes for multi-structured data with a team of certified experts. Design optimization of data warehouses and databases is one of our services. We have experience handling large volumes of data processing, Real-Time streaming, Pub/Sub messaging and Batch Processing.

Data Processing

Besides implementing scalable data-driven solutions, we also offer real-time and batch data pipelines and processing. In addition, we also provide data quality and standardization services. Furthermore, we also offer our clients Data Integration & Maintenance, Data Warehouses and Data Lakes installation, Data Transformation and Data cleansing services.

Cloud data engineering

In addition to defining your AI vision, our data engineers will help you build a data strategy that aligns cloud, technology, & governance pillars, choosing the right technology & modernizing your data platforms.

  • Cloud assessment
  • Application and platform modernization
  • Cloud governance and operating model
  • Cloud enablement and managed services (Scaled DevOps and MLOps)
  • Data lakes, cloud data warehouse and BI enablement

Azure Data Explorer

Integrate Azure Data Explorer to gain real-time, actionable analysis that helps deliver innovative products and superior customer experiences.

Azure Data factory

Integrate all your data with Azure Data products that allow you to easily build hybrid pipelines such as ETL and ELT, and other data integration tools.

Azure Data bricks

Manage and monitor your project efficiently with Azure data bricks solutions and automate your operations with machine learning-based labeling techniques.

Azure stream analytics

Perform your most complex operations with ease and tick off production stages faster with easily constructed data pipelines by implementing Azure stream analytic solutions.


Automate your tedious data operations by integrating advanced data tools.

End-to-end data engineering services and solutions that accelerate time-to-value and reduce cost-of-quality.


Kafka is an open-source streaming software that is
used for various data
needs and data management solutions.

Azure synapse

Build unified, secure & scalable data architectures & better manage, monitor & maintain your big data with Azure synapse solutions.


Automate your tedious data operations by integrating advanced data tools.

End-to-end data engineering services and solutions that accelerate time-to-value and reduce cost-of-quality.

Case Studies


The Client wanted to replace the already existing legacy AMIS App and build new design features within the paradigm of Unilever Make Digital Apps Program. They were looking for an intuitive user interface to load the Factory OEE Losses, HR KPI’s – Labour productivity related, Output reliability loss tree and Integrated Analytics dashboard.


MDCS replacement of AMIS would bring the below advantages.

  • MDCS Digital App follows Unilever standards
  • Built-in validations nearly 40+ data validations which makes the data captured is clean and healthy for reporting.
  • Scalable to integrate data with other “Make and supply chain digital apps” like DFOS, NGTW, MCOF, SOP etc (Future release)
  • MDCS has preconfigured reports – provides immediate insights into Factory performance.
  • MDCS app has integrated reports developed through Power BI
  • MDCS would be integrated with DFOS as per of next level enhancements, soon the OEE Loss data can be automatically populated.


One of the largest FMCG companies approached us seeking a CRQS assessments module to measure "products" against Consumer Relevant Quality Standards (CRQS). A Consumer & Customer Relevant Quality Standard defines standardized consumer, shopper and/or customer relevant properties for an item. All standards use a typical format and follow an agreed naming that is convenient for easy identification. Items that are covered are consumer units, retail ready packaging (RRP), displays, cases, SKu’s and pallets.
The assessments are done at different places in the extended supply chain but must always be done using the global process and standards.


Carbynetech conducted quick assessment of use-case and could quickly draw out the features, user stories and wireframes with the manufacturing experience of similar domain companies CRQS assessment of on pack is established in all the factories and assessed every shift and reported in hardcopy logbooks(Maintained Hourly in every shift). Shift DPMU is calculated for every SKU from every line in the factory as well as a factory DPMU is declared and shown as a report in a centralized dashboard.
The solution covered the below modules:

  • Production Quality Checks
  • Defect Trend Analytics
  • D-Incident Tracking and Monitoring


A leading chemical and fertilizer manufacturer sought to capitalize on advanced analytics for competitive advantage. Nevertheless, without a clear understanding of what data can do for their organization, how to effectively store and harness that data and the right approach to such endeavours, their efforts may end up doing more damage than good. Considering this, what is the most effective tool to help a company gain insights from its data? They needed a data warehouse to support reporting, analytics, and other advanced uses.


Upon clearly understanding their business requirement, We suggested an ETL framework that forms the foundation for data analytics and machine learning workstreams. This ETL process cleans and organizes data according to business rules so that it meets specific business intelligence needs, such as monthly reporting, but it can also offer more advanced analytics, which may improve back-end processes or end-user experiences.
The ETL services we offer:

  • Extract data from legacy systems
  • Cleanse the data to improve data quality and establish consistency
  • Load data into a target database