LLM integration
Structured model outputs, provider routing, validation, prompt versioning, and cost-aware execution.
AI integration that behaves like production software.
I add AI capabilities where they create measurable value, then engineer the validation, fallbacks, review paths, and data boundaries required to operate them safely.
What I deliver
Focused engineering, end to end.
Knowledge workflows
Retrieval, document processing, classification, extraction, and human-reviewed recommendations.
AI automation
Background pipelines with checkpoints, retries, monitoring, and explicit handling of uncertain results.
Good fit for
Projects where reliability matters.
- Teams adding AI to an existing product
- Businesses processing repetitive knowledge work
- Products requiring controlled multi-provider AI
QA Engine
Production-scale backend system to autonomously generate and validate technical MCQs. Reduced generation time by 90%.
AI Stock Price Predictor Demo
Machine learning model that predicts next-day open and close stock prices using historical OHLCV market data. Features data preprocessing, feature scaling, and model evaluation with MAE/RMSE metrics.
View project ↗StudySync
Full-stack collaborative learning platform with role-based system, real-time chat via WebSockets, file uploads to Cloudinary, and JWT authentication. Teachers upload notes, students browse by branch/year/semester.
View project ↗