Microsoft Data & AI Services

Harness the power of your data at scale, with enhanced performance and endless possibilities, using Azure data services.

As a Certified Microsoft Partner Specialist in Data & AI, Sullexis has a rich history of guiding and assisting its clients to generate value from their cloud investments.  Whether deploying your next analytics capability or building out your first AI use case, Sullexis can help from planning and design to delivery and adoption.

How Sullexis Can Help 

Design and Build Data Ingestion for Analytics and Visualizations


Sullexis excels in crafting streamlined data ingestion pipelines specifically geared towards analytics and visualizations. We understand the critical role data ingestion plays in successful analytics endeavors. By collaborating closely with clients, we identify diverse data sources like IoT devices, document libraries, and transactional databases, prioritize quality and reliability, and deliver scalable solutions that can be used throughout the organization.

With our expertise in data engineering, we empower our clients to harness their data for informed decision-making. Our collaborative approach prioritizes scalability, efficiency, and flexibility from conceptualization to deployment. Whether it’s real-time streaming data or batch processing, our tailored solutions enable clients to extract maximum value from their data investments, driving innovation and competitive advantage in today’s dynamic market.


Implement AI-Backed Analytics & Solutions

AI-backed analytics is a newer tool in the analyst’s toolkit enabling predictive analytics, driving pattern analysis, and optimizing business processes and productivity. Whether it’s a simple linear regression analysis for financial forecasts, an advanced ensemble methodology to address complex predictive analytics problems, or a Generative AI deployment leveraging Large Language Models (llm), all AI use cases are data-driven and inherit the same problems of their prescriptive predecessors. The old adage of ‘Garbage in, Garbage out’ weathers every technological advancement, and Sullexis data expertise has continued to help our clients deliver AI-backed solutions.  

Often much of a company’s AI IP lives in a data scientist’s notebook on a laptop, presenting challenges to production readiness and scaling. Developed in a bubble, without proper engineering best practices, these valuable projects can sometimes slip through the cracks of IT management, causing support issues that eventually lead to scrapped projects and failed application hosting. Leveraging our decades of data management and engineering expertise, Sullexis has helped corporations implement well-engineered AI, focusing on the crucial, less glamorous aspects to free up client’s valuable data science expertise to focus on model development.


Application Integration and Data Migration Services

The only constant in IT is change. To remain competitive, you must continually address upgrades and integrations with new applications and data migrations. Data is the key to any system migration or integration. We are data experts with deep experience in planning, defining, and implementing data integrations and migrations.


IoT Hub Services

A central message hub for communication between devices and backend solutions is a critical piece of maximizing the value of IoT data.

Sullexis can help you establish your Azure IoT Hub, creating reliable and secure two-way communication. We extend your IoT solution from the cloud to the edge with device authentication, management, and scaled provisioning. Sullexis integrates IoT Hub with other Azure services for a complete, end-to-end connected environment around your assets and developed IoT analytics solutions.


Implement Microsoft Purview Data Catalog

As data volume and complexity grow, organizations struggle with maintaining visibility across enterprise information assets. Purview addresses this by inventorying data sets, standardizing metadata, and centralizing knowledge, enabling users to find and leverage organizational data effectively.