CRM Platform with AI Integration
Complete CRM platform developed to streamline lead management, sales processes, and customer relationships. Built with React 19, Django 5, PostgreSQL with pgvector, and supporting both cloud-based and local AI providers.
TL;DR
A fullstack CRM platform that combines traditional CRM functionality with advanced AI integration, real-time notifications, and comprehensive automation. Result: Complete CRM solution with AI integration and automation.
2 months
Development time
Solo project
Collaboration
Success
Project outcome
100%
Client satisfaction
The challenge
Companies often split lead tracking, deal data, and customer history across separate tools, which fragments information and makes the full sales pipeline hard to see at a glance.
My approach
I built a fullstack CRM on React 19 and Django 5, using PostgreSQL with pgvector for semantic search across leads and deals. A provider abstraction layer supports both cloud AI (OpenAI) and local AI (LM Studio), while Django Channels and Celery handle real-time updates and background jobs.
Technical features
Built with modern technologies and best practices for reliability and performance
Technology stack
Modern technologies and frameworks for optimal performance
Security and quality
Built with security best practices and quality assurance
Clean architecture
Well-structured codebase following industry standards
Performance
Optimized for speed, scalability, and user experience
Key features
AI-powered semantic search with pgvector
Real-time notifications over WebSockets
Workflow automation engine
CRM analytics dashboard with caching
Technologies used
Common questions
What makes this CRM platform different from a standard CRM?
It adds AI-powered semantic search over leads and deals using pgvector, real-time notifications over WebSockets, and a workflow automation engine, on top of standard CRM features like pipelines and activity tracking.
Can the CRM run without a cloud AI provider?
Yes. The AI layer supports both cloud-based providers like OpenAI and a local option through LM Studio, so a company can choose based on cost, privacy, or infrastructure preferences.
Project impact
The platform gives one place for leads, deals, and customer history, with AI-assisted search and recommendations layered on top. Its modular structure means individual parts can be updated without touching the rest of the system.