lead-scoring

Lead Scoring is such a powerful metric when it comes to quantifying the lead & it is nowadays used by every CRM. In this repository, we are going to take a look at the UpGrad lead scoring case study and see how can we solve this problem through several supervised machine learning models.

Lead-scoring analysis with ranking metrics, precision-recall tradeoffs, and conversion modeling.

Open-source revenue intelligence — detect buying signals from your PostHog + CRM data and route the warmest leads to sales. Self-hostable. The open-source alternative to Pocus and Common Room.

An end-to-end enterprise-grade example of working a data science problem.

Typescript library to access Faraday's API infrastructure for B2C predictions https://www.npmjs.com/package/@fdy/faraday-js

Building a end-to-end lead scoring machine learning example with Jupyter, Sagemaker, MLflow, and Booklet.ai.

AI-powered Lead Qualification & Routing System built with n8n, Gemini and Python.

In this project, I leverage machine learning models including Logistic Regression, Decision Tree, Random Forest, XGBoost, CatBoost, and LightGBM to predict customer lead scoring. I apply WOE and SHAP for feature selection and use Optuna for hyperparameter turning, aiming to identify potential lead customers effectively.

50-state UCC public-records intelligence — fresh, enriched, scored MCA / financing leads via dashboard, REST API, and CLI.

AI-powered Reddit Lead Finder & Intent Scorer using n8n and Gemini AI. Automatically scans subreddits, analyzes lead intent, and exports to Google Sheets. 🚀

Google Maps Leads Scraper - python

Self-hosted AI Go-To-Market platform: 5 autonomous AI agents for ICP scoring, outreach personalization, deal intelligence, and churn prediction.

Trained a model that estimates if a lead is likely to be converted based on lead behavior in historical customer data using ML.

Turns messy leads from any source (Facebook, Instagram, Google Forms, landing pages) into clean, deduplicated, scored leads in one schema. Each lead gets a 0–100 score, a plain-English reason, and a next action. Fixes its own code when it breaks. 100% free and runs fully local.

An Automated Lead Management and CRM do star It If you like It.

⚡ AI-powered email verification and lead intelligence system built for near-zero bounce rates. Uses SMTP checks, DNS analysis, and risk scoring to ensure only high-quality, deliverable leads for safe, enterprise-grade outreach.

B2B Lead Intelligence Platform

AI-powered CRM & Sales Analytics dashboard built with Streamlit. Includes customer segmentation, KPI tracking, AI insights, and automated email notifications using SendGrid.

AI-powered GTM intelligence, lead scoring, personalized outreach, and HubSpot CRM automation built with n8n, Apollo MCP, Firecrawl, and Groq AI.