Work That Ships to Production

Problem

Financial institutions manually assess loan risk — slow, inconsistent, and prone to human bias.

Result

ML model predicting credit default with 94%+ accuracy, deployed as a production REST API.

Problem

ML models built in notebooks die on laptops — no versioning, no retraining, no monitoring.

Result

Full MLOps pipeline with automated retraining, DVC versioning, MLflow tracking, and CI/CD deployment.

Problem

Shopify merchants have 699 chat apps — none can process refunds, update inventory, or deploy on WhatsApp natively.

Result

Built a full no-code AI agent platform with Shopify native actions, WhatsApp/Telegram/Slack deployment, and flat predictable pricing.

Problem

Content teams spend days writing blog posts manually — topic research, outlining, drafting, and SEO optimization all done by hand.

Result

Full blog automation pipeline with human-in-the-loop review: automated topic discovery, relevance scoring, LLM outlines with approval workflow, and SEO-optimized final generation.

Problem

Dermatology diagnosis is manual, slow, and inconsistent — doctors spend significant time on visual assessment that AI can automate.

Result

YOLO-based acne segmentation model achieving 90%+ accuracy, with React frontend for image upload and real-time webcam capture, deployed via FastAPI + Docker.

Problem

Existing search systems use single models — complex queries require multi-model reasoning and retrieval.

Result

Research-grade multi-model search system with 92.6% retrieval accuracy using LLM orchestration.

Problem

Teams waste weeks rebuilding the same MLOps infrastructure — no standard, no repeatability.

Result

Reference MLOps implementation covering the full lifecycle: data to train to evaluate to deploy to monitor.

Problem

Marketing teams spend budgets on customers who were already leaving — no predictive signal exists.

Result

Full EDA and churn prediction model identifying at-risk customers 30 days before cancellation.

Problem

Mental health support is inaccessible and expensive — most people cannot afford or access a therapist.

Result

Real-time conversational AI therapist with emotional intelligence, session memory, and crisis detection.

Problem

Generic chatbots hallucinate and ignore company-specific knowledge — useless for real business needs.

Result

Production RAG system that ingests PDFs, URLs, and docs — answers questions grounded in real data.

Problem

Static chatbots can only answer questions — businesses need agents that take real actions autonomously.

Result

LangGraph-powered agent with tool use, memory, and multi-step reasoning for autonomous task execution.

Problem

Customer support teams are overwhelmed with repetitive queries that drain time and increase costs.

Result

Deployed chatbot handling user queries with intent classification and dynamic response generation.

Problem

Businesses lose customers without warning — by the time they notice churn, it is too late to act.

Result

End-to-end churn prediction pipeline with automated retraining and REST API for real-time scoring.

Problem

Job boards are flooded with fraudulent postings — job seekers waste time and risk being scammed.

Result

NLP classifier detecting fake job listings with 96% precision using BERT-based feature extraction.

Problem

Pre-trained captioning models generate generic captions — domain-specific images need custom fine-tuning.

Result

Fine-tuned transformer model generating accurate context-aware captions for domain-specific images.

Problem

Language barriers block real-time communication — existing tools add 3 to 5 second delays.

Result

Real-time speech-to-speech translation pipeline with sub-second latency using Whisper and NMT.