Burhan Azeem

Designed and implemented an automated SAP onboarding and offboarding system to streamline HR and IT employee lifecycle workflows. Built backend services for user provisioning using Active Directory, email setup, and automated access control. Developed scalable REST APIs to connect SAP with internal enterprise systems and third-party services, improving onboarding efficiency by automating repetitive operations.

Developed REST APIs and data integration components to connect multiple vendor systems into a unified building management platform. Built real-time React dashboards for operational monitoring and designed data pipelines that combine SQL data, NoSQL sources, and external API data. Improved analytics workflows with AI-assisted query and reporting mechanisms and supported high-performance backend aggregation across distributed services.

Developed backend services for a real-time chat application and supported a dynamic frontend through RESTful APIs. Built and customized e-commerce solutions using WordPress and Odoo. Focused on performance improvements and scalable backend architecture while resolving production issues affecting reliability.

Developed an AI-powered surveillance solution that performs face recognition and detects weapons from CCTV streams. Applied computer-vision techniques for real-time threat monitoring. Implemented backend services to process and analyze high-volume video data streams for timely insights.

Developed a scraping and analytics platform to identify real estate investment opportunities based on configurable criteria. Implemented automated data collection and filtering pipelines across multiple data sources. Added AI-based evaluation logic to assess properties using profitability and trend signals and delivered dashboards for decision support.

Built an LLM-enabled system for natural-language querying over structured datasets using RAG-style retrieval. Implemented embedding pipelines and semantic search to return context-aware results for user questions. Designed workflows that generate automated insights and reduce manual analysis effort while supporting scalable query execution.

Created an automated pipeline to retrieve and process voice-agent conversation data via paginated REST APIs. Built LLM- and NLP-based analytics to extract insights such as sentiment, task status, escalation signals, delays, and interruption patterns. Implemented asynchronous ingestion and processing with structured JSON outputs, including error handling and retry mechanisms.