Production AI Showcase
A selection of production-grade solutions I've engineered to solve critical business problems.
Counterpoint POS: An AI-Powered Point-of-Sale System
Increased transaction speed by 30% and eliminated inventory-related revenue loss for a mid-market retail client.
Live demo of the application.
The Challenge: A retail business was losing significant revenue due to slow, error-prone manual sales logging and frequent inventory discrepancies.
The Solution: Architected and deployed a bespoke, intelligent POS system with an NLP-driven voice/text interface to fully automate sales and inventory updates with near-zero error.
Production Stack: Angular, TypeScript, Python, Django, Django REST Framework, PostgreSQL, Redis, Nginx, Docker, Together AI (for Whisper & Language Models)
Momentum
Reduces complex financial analysis from 20 minutes of manual spreadsheet work down to a <3 second conversational query.
Live demo of the application.
The Challenge: Freelancers and SMBs lack the tools to accurately forecast cash flow and make proactive financial decisions.
The Solution: Built a full-stack SaaS application featuring a real-time analytics dashboard and a conversational forecasting module powered by a LLaMA 3.3 70B LLM.
Production Stack: React, Next.js, FastAPI, SQLite, Prophet, LLaMA
Joule: Your AI Smart Home Monitor
Enables homeowners to ask natural-language questions about their energy consumption and view data via a real-time dashboard. The system is designed to provide actionable insights for reducing waste and utility bills.
Live demo of the application.
The Challenge: Homeowners lack real-time visibility into their energy consumption, making it difficult to understand usage patterns and identify opportunities for savings.
The Solution: This project is a functional prototype of an AI-powered Smart Home Energy Monitor. It ingests real-time energy telemetry data, visualizes usage over time on a single-page React dashboard, and uses a conversational AI to answer user questions with structured data and summaries.
Production Stack: Python 3.11 (FastAPI), React 19 (Vite), PostgreSQL (TimescaleDB), Docker, Mistral LLM
Vantage: AI Market Intelligence
AEnabled the client to identify 3 major market opportunities within the first month, leading to a 40% increase in qualified leads and positioning them ahead of competitors in emerging market segments.
Live demo of the application.
The Challenge: A growing MarTech agency needed to monitor competitor activities, track market trends, and identify emerging opportunities across multiple industries in real-time, but existing tools were fragmented, expensive, and lacked predictive capabilities.
The Solution: Built a comprehensive AI-driven dashboard that combines real-time web scraping, sentiment analysis, and predictive modeling to deliver actionable market intelligence. The platform processes live data from multiple sources and generates executive-ready insights with confidence scoring and trend predictions.
Production Stack: Node.js/TypeScript, React/Next.js, Redis, WebSocket real-time updates, Together AI, Advanced NLP models, Automated web scraping infrastructure
The Proposal Engine
Reduced proposal generation time from 4 hours to 15 minutes and eliminated pricing errors for a client.
Live demo of the application.
The Challenge: An APAC-based digital agency struggled with a chaotic sales process. Their proposals had inconsistent pricing and slow manual approvals, which delayed closing deals.
The Solution: Engineered a Deal Desk Engine that automates the creation of accurate, rule-based proposals and SOWs. The system enforces pricing from a central pricebook, inserts pre-approved legal clauses, and flags proposals for manager review based on custom business rules.
Production Stack: Next.js, FastAPI, LangGraph, Together AI, Redis, WeasyPrint, Vercel, Railway
The Brand Engine
Increased a client's A/B testing cadence by 5x and enabled same-day campaign launches for new products.
Live demo of the application.
The Challenge: A fast-growing DTC e-commerce brand needed to scale content creation for social media without sacrificing brand consistency, which was a major bottleneck for their marketing team.
The Solution: Built an agentic system that takes a product catalog and brand guide to autonomously generate batches of on-brand ad creatives. The agent acts as a virtual art director, writing expert-level prompts to ensure all images and copy are 100% on-brand.
Production Stack: Next.js, FastAPI, LangGraph, Together AI (Image & Text Models), Redis, Vercel, Railway
The Skill Verification Engine
Reduced a client's screening time by 90% and increased the quality of candidates reaching the final interview stage by 40%.
Live demo of the application.
The Challenge: A rapidly scaling tech startup was overwhelmed by hundreds of applications per role. Good candidates were being missed, and they were concerned about unconscious bias in their screening process.
The Solution: Developed a system that goes beyond resumes to find the best talent. The agent first anonymizes all applications, then autonomously issues and evaluates unique, role-specific skills challenges to verify real-world capabilities in a fair and cheat-proof way.
Production Stack: Next.js, FastAPI, LangGraph, Together AI, PyMuPDF, Redis, Vercel, Railway
R&D Showcase
Exploring the next wave of AI applications. These are solution blueprints I am actively developing to address emerging business needs.
Precedent
Problem: The sheer volume and complexity of case law presents a significant challenge for legal professionals.
Approach: Developing a tool using advanced NLP to parse and provide accurate summaries of legal documents.
Business Value: This solution blueprint aims to make case law more accessible, saving valuable time for legal experts.
Synapse
Problem: The manual process of conducting literature reviews is a significant bottleneck for medical and scientific researchers.
Approach: Engineered an NLP pipeline that integrates with the PubMed API to generate concise research briefs.
Business Value: This tool demonstrates how AI can drastically accelerate medical research.
Curriculum Scribe
Problem: Educators are burdened by the time-consuming tasks of creating high-quality, tailored lesson plans, quizzes, and assignments.
Approach: An AI-powered platform to assist with lesson planning and generate educational materials.
Business Value: A practical, valuable tool for educators that allows them to focus on student interaction rather than administrative work.
Keystone
Problem: Individuals struggle with self-discipline and maintaining consistent habits for personal growth.
Approach: A mobile-first application that acts as a personalized AI coach to create tailored growth plans.
Business Value: A consumer-facing app to support mental wellness and development through an AI-driven accountability system.
Kindred
Problem: Seniors often face challenges with loneliness and managing daily tasks.
Approach: A voice-first AI assistant for smart speakers, designed with accessibility in mind to handle reminders and facilitate communication.
Business Value: Addresses a key social need by enhancing quality of life for seniors and offering a scalable solution for remote care.
Coda
Problem: Musicians and content creators often face creative blocks when composing music.
Approach: An AI tool that suggests melodies, harmonies, and chord progressions based on user inputs.
Business Value: Democratizes music creation by making professional composition tools accessible to artists of all skill levels.