AI-powered travel planning and itinerary optimization with Next.js 16, Vercel AI SDK v7, Supabase/pgvector, and Upstash Redis/QStash.
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Oct 13, 2026 - TypeScript
AI-powered travel planning and itinerary optimization with Next.js 16, Vercel AI SDK v7, Supabase/pgvector, and Upstash Redis/QStash.
๐งณ A state-of-the-art multi-agent travel planning system powered by OpenAI Agents SDK and LangGraph orchestration. Leverages Stagehand/Playwright for browser automation, Supabase for data persistence, and Firecrawl/Tavily for intelligent research.
Karpiu is a package designed for marketing mix modeling by calling Orbit from the backend. Karpiu is still in its beta version. Please use it at your own risk.
Marketing Mixed Modelling using PyMC3-Marketing
Simba โ Bayesian Marketing Mix Modeling (MMM) platform. Media attribution, budget optimization, incrementality measurement, and scenario planning. Built on PyMC-Marketing. No-code, fully transparent, enterprise-ready.
AI-powered campaign intelligence platform for media buyers. Consolidate Meta, Google, TikTok & Taboola data, uncover root causes, optimize budgets, generate executive briefs, and scale winning campaigns faster.
The Earth Optimization Machine!
Comprehensive performance marketing optimization strategies covering modern paid advertising, ROI maximization, and campaign optimization methodologies. Maximize marketing performance and profitability.
MARFOR Marketing Mix Modeling: a Claude plugin for MMM data checks, budget scenarios and robust allocation
๐๐ Comprehensive GeoSpatial environmental data analysis, focusing on dissolved carbon & greenhouse gases. Includes advanced data processing, analysis, and budget optimization.
This repository contains the links to Medium Articles written by me on topics like Digital Marketing Analytics, Data Science & Deep Learning
Multi-agent ad investment framework built with LangGraph + Groq (LLaMA-3.3-70B), simulating budget optimization, bid strategy, and risk validation across Amazon and Flipkart ad channels.
A Marketing Mix Modeling (MMM) project using Python to analyze channel performance, calculate ROI, and simulate marketing budget changes for better business decisions. Includes a trained Linear Regression model, ROI analytics, and a Flask API for revenue prediction.
A new package that analyzes user-provided text descriptions of their monthly expenses and income to generate a structured affordability assessment. It categorizes spending, identifies potential saving
Bayesian Marketing Mix Model built with PyMC-Marketing to measure the ROAS of TV, OOH, print, Facebook and search, and reallocate the marketing budget to get more sales from the same spend.
Bayesian Marketing Mix Modeling system โ calibrated media attribution, budget optimizer, FastAPI backend and React dashboard. Built with PyMC, Docker-ready.
๐ Google Ads AI ๅฏ้ฉพ้ฉถ โ ๆ็ดข่ฏไธ้่ฏไผฐใๅฆๅฎ่ฏ็ญ้ใ้ข็ฎไผๅใ่ดฆๆท่ฏๆญ | AI copilot for Google Ads
๐งฎ Analyze time series to uncover causal links and find optimal values, enabling evidence-based decisions for health, finance, and policy.
Enterprise B2B multi-touch attribution and budget optimization engine built with Polars, DuckDB, Pydantic v2, Gemini structured output, and Streamlit.
Bayesian MMM๊ณผ ์ต์ ์์ฅ ํธ๋ ๋๋ฅผ ํ์ฉํด ๋ค์ ๋ถ๊ธฐ ๋ง์ผํ ์์ฐ ๋ฐฐ๋ถ์ ์ถ์ฒํ๊ณ , ์์ ์ฑ๊ณผ์ ๋ถํ์ค์ฑ์ ๋น๊ตํ๋ ์๋ฎฌ๋ ์ดํฐ
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