Selected work across AI engineering, data engineering, and software engineering. Each card links to the case study + code where available.
Co-founded an end-to-end GenAI platform that automates the innovation workflow for Consumer Packaged Goods companies, from idea prototype through to production-ready concept. Full-stack React + Python + LLM integration, shipped to early customers.
Designed a self-service platform for defining, running, monitoring, and investigating data-quality checks across distributed data workloads.
Designed an AI-assisted review workflow that checks proposed event schemas against documented contracts and produces a structured, evidence-backed review.
Designed Model Context Protocol integrations that give AI agents structured access to location, routing, and traffic-analysis capabilities.
Contributed to an agent toolkit that lets LLM applications interact with mapping capabilities through structured, typed tools.
Designed a multi-agent prototype for answering traffic-analysis questions with scoped tools, structured evidence, and a single grounded response.
Hackathon prototype that turns an address into a structured neighbourhood profile using a multi-step, tool-using AI workflow.
Designed a planner-executor system that converts natural-language location requests into grounded, multi-step tool calls and explainable results.
Refactored event-processing pipelines into a governed, queryable transformation layer for trusted operational analytics.
Built a Python validation library that turns sample events into editable contracts with reusable field-level quality rules.
Co-founded a news-aggregation platform that uses GPT models to synthesise stories from multiple sources, removing single-source bias. Plus a RAG-based study chatbot for students preparing for India's public-service exams: embeddings pipeline, vector search, and a conversational interface.
Refactored a fragmented set of analytics pipelines into a reusable Python template with consistent ingestion, transformation, testing, and operational behaviour.
Built a typed API layer that turns analytical warehouse queries into reliable, self-service usage reporting for product and support teams.
Architected an enterprise data lake with a metadata-driven PySpark framework, schema versioning, and reusable data-quality patterns.
Reusable PySpark library that standardised reading, writing, configuration, and error handling across common enterprise data stores.
Led development of a configurable data-quality platform with reusable connectors for profiling, validation, and reconciliation across varied sources.
Led development of a production document-classification and entity-extraction system, with reproducible training, evaluation, and deployment workflows.
Improved the reliability and throughput of data pipelines by reworking bottlenecks, parallelism, storage formats, and streaming hand-offs.
Built backend services and REST APIs for an enterprise user-management platform, working closely with product stakeholders in an Agile delivery process.