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Nwadiaro Miracle
AI Agent & Automation Developer | LLMs, ML & API Integration
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Nwadiaro is ready for their next project!
Smart Meeting Notes
An AI-powered agentic meeting assistant that autonomously captures, transcribes, and summarizes meetings in real-time whether from uploaded files, URLs, or live browser sessions. It detects meetings automatically, transcribes without user intervention, and delivers structured summaries with action items, decisions, and next steps.
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EDU Hub is a student-focused social media app pitched as a place to share ideas, collaborate on projects, connect with educators, and access educational resources aimed at high school, college, and graduate students.
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AI Automation Dashboard — Lead Enrichment Pipeline
Built a full automation dashboard that runs a multi-step lead enrichment pipeline. New leads are automatically enriched via Clearbit, scored by GPT-4o, routed to the right rep, and synced to HubSpot CRM — all without human input. Tracks 8,400+ monthly tasks, 142 hours saved, and 99.1% success rate across 12 active workflows. Stack: LangChain, OpenAI GPT-4o, HubSpot API, Clearbit, Gmail API, Python.
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Voice AI Assistant — Calendar & Email Agent
Built a voice-powered AI assistant that listens to spoken commands and takes real actions. Integrates with Google Calendar and Gmail to fetch meetings, read emails, and summarize content in real time. Uses GPT-4o Realtime API for ultra-low latency voice responses. Stack: LangChain, OpenAI GPT-4o Realtime, Google APIs, Python.
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LangGraph Customer Support Agent
Built a stateful customer support agent using LangGraph. Classifies user intent (billing, technical, general), routes to the right sub-agent, checks if resolved, and escalates to a human if needed. Full conditional branching with persistent state. Stack: LangGraph, LangChain, ChatOpenAI GPT-4o, Python.
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RAG Pipeline — AI Document Q&A System
Built a RAG pipeline that lets users query their own PDF documents using natural language. Ingests, chunks, and embeds docs into a vector store (ChromaDB), then retrieves the most relevant chunks to answer questions via GPT-4o. Stack: LangChain, OpenAI Embeddings, ChromaDB, Python.
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