budget-optimization

AI-powered travel planning and itinerary optimization with Next.js 16, Vercel AI SDK v7, Supabase/pgvector, and Upstash Redis/QStash.

🧳 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 — 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.

The Earth Optimization Machine!

Comprehensive performance marketing optimization strategies covering modern paid advertising, ROI maximization, and campaign optimization methodologies. Maximize marketing performance and profitability.

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.

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.

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 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 Modeling system — calibrated media attribution, budget optimizer, FastAPI backend and React dashboard. Built with PyMC, Docker-ready.

🚀 Google Ads AI 副驾驶 — 搜索词三重评估、否定词筛选、预算优化、账户诊断 | AI copilot for Google Ads

Enterprise B2B multi-touch attribution and budget optimization engine built with Polars, DuckDB, Pydantic v2, Gemini structured output, and Streamlit.

🧮 Analyze time series to uncover causal links and find optimal values, enabling evidence-based decisions for health, finance, and policy.

🌍🔍 Comprehensive GeoSpatial environmental data analysis, focusing on dissolved carbon & greenhouse gases. Includes advanced data processing, analysis, and budget optimization.

MOCA-Net: Novel neural architecture with sparse MoE, external memory, and budget-aware computation. Real Stanford SST-2 integration, O(L) complexity, 96.40% accuracy. Built for efficient sequence modeling.

End-to-end marketing analytics project using A/B testing, ROI analysis, Tableau dashboards, and budget optimization.

Excel/@risk Monte Carlo model comparing 58 marketing-budget allocations under uncertain conversion, click cost, and purchase value.