Skip to content

Production-ready AI-powered CRM with 6 autonomous agents for lead qualification, email intelligence, sales pipeline, customer success, meeting scheduling, and analytics

Notifications You must be signed in to change notification settings

KlementMultiverse/ai-crm-agents

Repository files navigation

🤖 AI-Powered CRM with Agentic Workflows

Production-ready CRM system powered by multi-agent AI architecture

🎯 Overview

An intelligent CRM system that uses autonomous AI agents to handle customer relationship workflows automatically. Each agent specializes in specific tasks and collaborates to provide a seamless customer experience.

🏗️ Architecture

6 Autonomous Agents

  1. Lead Qualification Agent 🎯

    • Scores incoming leads automatically
    • Routes high-value prospects to sales
    • Enriches contact data from public sources
    • Identifies buying signals
  2. Email Intelligence Agent 📧

    • Drafts personalized responses
    • Sentiment analysis on customer emails
    • Auto-categorization and prioritization
    • Smart follow-up suggestions
  3. Sales Pipeline Agent 💰

    • Tracks deal progress
    • Predicts close probability
    • Identifies stalled deals
    • Recommends next actions
  4. Customer Success Agent 🎉

    • Monitors customer health scores
    • Detects churn risk
    • Triggers retention workflows
    • Upsell/cross-sell opportunities
  5. Meeting Scheduler Agent 📅

    • Smart calendar management
    • Context-aware scheduling
    • Automatic meeting prep
    • Follow-up task creation
  6. Analytics Agent 📊

    • Real-time dashboards
    • Predictive analytics
    • Performance insights
    • Custom reports

🚀 Features

Core CRM

  • Contact & company management
  • Deal pipeline tracking
  • Task & activity logging
  • Email integration
  • Calendar sync

AI-Powered

  • Automatic lead scoring
  • Intelligent email responses
  • Sentiment analysis
  • Churn prediction
  • Sales forecasting
  • Smart notifications

Agentic Workflows

  • Autonomous lead nurturing
  • Auto-follow-up sequences
  • Deal health monitoring
  • Customer success automation
  • Meeting coordination
  • Data enrichment

🛠️ Tech Stack

Backend:

  • Python + FastAPI
  • PostgreSQL database
  • Redis for caching
  • Celery for async tasks

AI/ML:

  • LangChain for agent orchestration
  • Claude/GPT-4 for intelligence
  • Vector DB for context storage
  • Sentiment analysis models

Frontend:

  • React + TypeScript
  • TailwindCSS
  • Real-time updates (WebSocket)
  • Charts & analytics

Integrations:

  • Gmail/Outlook API
  • Google Calendar
  • LinkedIn enrichment
  • Slack notifications
  • Zapier webhooks

📋 Agent Workflows

Lead Qualification Flow

New Lead → Data Enrichment → Scoring → Routing → Auto-Email → CRM Entry

Email Intelligence Flow

Incoming Email → Sentiment Analysis → Categorization → Draft Response → Human Review

Deal Management Flow

Deal Created → Health Monitoring → Risk Detection → Action Recommendations → Auto-Followup

Customer Success Flow

Customer Activity → Health Score → Churn Risk → Retention Trigger → Success Team Alert

🎨 UI Components

  • Dashboard - Real-time metrics & agent activity
  • Contacts - Enriched contact profiles
  • Deals - Visual pipeline with AI insights
  • Inbox - Smart email management
  • Calendar - AI-scheduled meetings
  • Analytics - Predictive insights
  • Settings - Agent configuration

📊 Key Metrics

  • Lead-to-customer conversion rate
  • Average deal cycle time
  • Customer lifetime value
  • Churn prediction accuracy
  • Email response time
  • Agent automation rate
  • Revenue forecast accuracy

🔐 Security

  • End-to-end encryption
  • Role-based access control
  • API authentication (JWT)
  • Audit logging
  • Data privacy compliance (GDPR)

🚀 Quick Start

# Install dependencies
pip install -r requirements.txt

# Setup database
python setup_db.py

# Run migrations
alembic upgrade head

# Start backend
uvicorn main:app --reload

# Start agent workers
celery -A agents.worker worker --loglevel=info

# Start frontend
cd frontend && npm start

🔄 Agent Communication

Agents communicate via:

  • Message Queue (RabbitMQ/Redis)
  • Shared State (Redis)
  • Event Bus (pub/sub)
  • API Calls (RESTful)

📈 Scaling

  • Horizontal scaling with Docker/Kubernetes
  • Load balancing for API
  • Database read replicas
  • Async task distribution
  • CDN for static assets

🎯 Use Cases

  1. SaaS Companies - Automate customer onboarding
  2. Sales Teams - Intelligent lead qualification
  3. Customer Success - Proactive churn prevention
  4. Account Executives - Smart deal tracking
  5. Marketing - Lead nurturing automation

🔮 Future Features

  • Voice AI for calls
  • WhatsApp integration
  • Advanced forecasting
  • Multi-language support
  • Mobile app (React Native)
  • Custom agent builder (no-code)

Built with ❤️ for modern sales teams

License: MIT Status: 🚧 In Development Last Updated: 2025-10-09

About

Production-ready AI-powered CRM with 6 autonomous agents for lead qualification, email intelligence, sales pipeline, customer success, meeting scheduling, and analytics

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Contributors 2

  •  
  •