In-Depth Case Studies
Detailed breakdowns of complex problems, strategic logic, and the resulting business impact.
Scaling Acquisitions with AI Lead Generation
Project Overview
Designed an end-to-end automated pipeline to eliminate manual prospecting, allowing the sales team to focus entirely on closing.
The Problem
The client’s sales team spent 80% of their time manually scraping data, verifying emails, and sending generic outreach messages. Conversion rates were stagnant at 2% and the team was burning out.
The Strategy
Implement a fully autonomous system that scrapes targeted data, enriches it via Clearbit, and uses an LLM to generate hyper-personalized intro emails tailored to each prospect's recent company news.
The Solution
Built a Python-backend integrated with OpenAI APIs and Make.com workflows. The system autonomously processes 10,000 leads weekly, scoring them based on proprietary ICP metrics before initiating sequenced outreach.
Business Results
- 300% increase in qualified sales meetings.
- 40 hours/week saved per SDR.
- 8.5% positive reply rate on cold outreach.
Modernizing a Legacy Financial Management Platform
Project Overview
Architected a responsive, real-time analytics dashboard to replace an outdated desktop application.
The Problem
The firm relied on a 15-year-old local software that crashed frequently and couldn't provide real-time asset pricing, leading to delayed trading decisions and client dissatisfaction.
The Strategy
Decouple the frontend from the legacy database using a secure Node.js middleware, and build a blazing-fast Next.js React frontend to consume real-time WebSocket data.
The Solution
Developed a distributed cloud-native architecture on AWS. The frontend utilizes React Query for aggressive state caching and Framer Motion for a fluid, premium user experience.
Business Results
- Zero downtime over the last 12 months.
- Data latency reduced from 5 minutes to <200ms.
- 100% adoption rate among the firm's 50+ wealth managers.