🚀 Santhosh Guntupalli
Data Engineer | AI/ML Specialist | Cloud & BI Architect
🔗 LinkedIn | 📧 Email | 💻 GitHub |
🚀 Featured Projects
Explore some of my most innovative and technical work — covering AI, data pipelines, dashboards, and real-time systems.
👥 GhostWriter Teams
Ghostwriter Teams is your local AI-powered creative department — built to help marketers, creators, and startups brainstorm, write, plan, and critique content like a full-scale agency.
Run locally with open-source models like LLaMA 2 or Mistral (via Ollama), it features five specialized agents working together to produce end-to-end campaign strategies, content calendars, rewrites, and branding insights — all without needing any paid API keys.
Ghostwriter Teams simulates a multi-agent marketing team where each AI agent specializes in a unique creative function:
- Zara – Creative Strategist
- Max – Content Architect
- Mira – Research Analyst
- Eva – Critic & Challenger
- Leo – Brand Guardian
You can brainstorm campaign ideas, generate structured content calendars, ask for rewrites, compare campaigns, and export your results — all through an intuitive Streamlit UI.
✨ Features
- AI Agents as Roles (Creative, Writer, Analyst, Critic, Brand Voice)
- Full Content Calendar Generation (Markdown tables with copy, dates, platforms)
- Campaign Brainstorming + Rewrite Assistant
- Multilingual Output (English, French, Hindi, Telugu, Japanese, and more)
- Local LLM Runtime with Ollama (LLaMA 2, Mistral, Gemma, etc.)
- No API Keys Required
- Export Campaigns as PDF, CSV, Markdown
- Timeline Visualizations with Altair & Plotly
- Campaign Comparison & Dashboard View
🚀 Example Use Case
“I want to launch an AI journaling app for moms. Help me plan 4 weeks of content on Twitter and LinkedIn.”
Ghostwriter responds with:
- A full platform-specific calendar of daily posts
- Emotional hooks and CTA optimizations
- Eva’s critique and rewrite suggestions
- Mira’s insights on trends, audience behavior, and timing
- Leo’s brand voice check to ensure tone alignment
Then, you export it all in Markdown, PDF, or CSV
Tech Stack: Streamlit · LangChain · Ollama · Local LLMs
⚡ GetGetLeads – AI Digital Marketing Agent
GetGetLeads is a powerful, AI-enhanced marketing automation platform built for modern teams and growth-focused individuals. It helps you generate and manage leads, track marketing performance, automate campaigns, and optimize SEO — all from a clean, intuitive dashboard.
Whether you’re a solo founder, marketing team, or agency, GetGetLeads simplifies the complexity of digital marketing with smart tools and automation powered by Supabase and OpenAI.
⚡ Key Features
- Lead Generation – Capture and score leads using AI-driven forms
- Analytics Dashboard – Visual insights into traffic, conversion, and ROI
- SEO + Keyword Tracking – Monitor rankings and optimize content
- Budget Management – Track ad spend, campaign costs, and performance
- Campaign Automation – Schedule and automate posts, emails, and outreach
- Customer CRM – Manage contacts, notes, and communication history
- Social Media Automation - upload social media content post, including tags based on users, interest, and schedule times
Stack: React · Supabase · Tailwind · OpenAI
✈️ GetGetPlaces – AI Travel Planning Agent
An intelligent NLP-powered travel planning platform with real-time weather, pricing, and smart routing. Engineered a full-stack AI/ML solution for real-time personalized itinerary generation, synthesizing multi-source APIs (weather, hotel, transport) using time-series analysis, Location and optimization models, demonstrating scalable predictive analytics deployment
Key Features:
- Natural language trip planning: “Plan 5-day Miami trip with $1500”
- ARIMA price forecasting (flights, hotels)
- Route optimization + travel time estimates
- Smart daily itineraries with weather forecasts
- PostgreSQL backend for trip data
Example Use:
“Plan a 7-day Orlando trip under $2500 focusing on theme parks and food” → Output: Day-wise schedule, attractions, maps, travel tips
Stack: PostgreSQL · ARIMA · OpenWeatherMap · LangChain
🎬 Movie Recommendation System
Built a content-based movie recommendation system using Python, Scikit-Learn, TensorFlow, NLTK, Pandas, and NumPy, applying NLP and similarity matching algorithms to analyze structured/unstructured data and generate personalized predictions.
Features:
- Content-based filtering on movie descriptions
- Enter a movie → Get top 5 similar films instantly
- Web app interface with Heroku deployment
Example Use:
Input: “The Matrix” → Output: Sci-fi action recommendations like “Equilibrium”, “Inception”, etc.
Stack: Flask · NLTK · Pandas · Scikit-learn · TF-IDF Vectorizer
🐍 Snake Game
A classic Snake game made using Python’s Tkinter GUI toolkit.
Highlights:
- Real-time movement and key-driven controls
- Score tracking and collision detection
- Minimalistic interface
Example Use:
Launch the app → Arrow keys to control → Eat food to grow → Avoid crashing into walls
🏓 Pong Game AI – NEAT
Trains an AI to play Pong using the NEAT (NeuroEvolution of Augmenting Topologies) algorithm.
Features:
- Evolution of neural networks via reinforcement
- AI adapts its paddle response to opponent’s movement
- Visualization of evolving agent skill
Example Use:
Launch → Watch AI learn after several generations → Compete against the bot
Stack: Python · NEAT-Python
📈 Real-Time Stock Market Analysis System
Designed a live stock market trend prediction pipeline using AWS services (EC2, S3, Glue, Athena) and Kafka, building real-time data streaming architectures to deliver predictive investment insights.
Features:
- Live data ingestion via Kafka
- Transformation with AWS Glue and Spark
- Query using Athena and visualize in dashboards
- Use case: financial alerting, intraday trend monitoring
Example Use:
Track tickers like AAPL, TSLA → Receive moving averages, trend shifts → Query on demand via Athena
Stack: AWS EC2 · Glue · Kafka · Athena · S3
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