What We've Built So Far

Challenge: A client needed to search and extract insights from hundreds of legal and policy PDFs without reading them manually.

Solution: Built a RAG pipeline using GPT-4o with custom chunking, hybrid vector + keyword search, and a clean React chat interface. Users ask natural language questions and get cited answers instantly.

Challenge: A startup's sales team was spending 3+ hours per day manually researching prospects before outreach calls.

Solution: Deployed a multi-agent system (CrewAI) that autonomously gathers company data, researches contacts, scores leads by fit, and drafts personalized first-touch emails — hands-free.

Challenge: A SaaS client had no visibility into which users were about to cancel, making proactive retention impossible.

Solution: Trained an XGBoost churn prediction model on 18 months of usage data. Deployed as a real-time API scoring users daily, with automated alerts when high-risk accounts are detected.

Challenge: A small e-commerce business was overwhelmed by repetitive customer inquiries that consumed their support team's time.

Solution: Built a context-aware support chatbot trained on their FAQs, product catalog, and past tickets. Handles 80% of inquiries autonomously and escalates complex cases to humans.

Challenge: A startup founder had a validated idea but no technical team. They needed a working MVP fast enough to raise a seed round.

Solution: We designed and built the full-stack MVP — React frontend, Python/FastAPI backend, PostgreSQL, and integrated AI features — from scratch in 3 weeks. Investor-demo ready.

Challenge: A small business was spending 10+ hours/week manually pulling data from 5 different tools to create weekly performance reports.

Solution: Built an automated data pipeline integrating all their tools, with an AI layer that generates plain-English summaries and highlights anomalies. Reports now arrive in their inbox automatically every Monday.