Transform your sales operations with an intelligent, self-organizing workspace that brings together customer intelligence, automated workflows, and AI-powered insights.

DealKit is an open-source, AI-native sales intelligence system that revolutionizes how sales teams operate. It automatically organizes customer data, generates contextual insights, and provides real-time alerts - all while maintaining itself through intelligent automation.

• 🤖 AI-Powered Intelligence: 30+ specialized AI agents for customer analysis, deal progression, and competitive intelligence
• 📊 Multi-Tier Reporting: Personal, team, and real-time pulse reports tailored to every role
• 🔄 Automated Data Collection: Continuous monitoring of Slack, email, and meeting platforms
• 📈 Smart Context Generation: 3-tier customer context (5K, 40K, 200K+ tokens) for every situation
• 🛡️ Self-Maintaining Structure: Built-in governance and audit systems preserve organization
• 🎯 Methodology-Driven: MEDDPICC qualification framework built into workflows

dealkit/
├── 🏢 customers/          # Intelligent customer profiles
├── 📊 reporting/          # Multi-tier analytics system
├── 🛠️ sales-toolkit/      # Battle-tested resources
├── ⚙️ workspace-setup/    # Automated integrations
├── 👤 personal/           # Individual workspaces
└── 🤖 .claude/            # AI agent definitions

# Clone the repository
git clone https://github.com/slng-ai/dealkit.git
cd dealkit

# Run the setup wizard
./workspace-setup/scripts/setup.sh

# Configure your integrations
export SLACK_API_TOKEN="your-token"
export SALESFORCE_CLIENT_ID="your-client-id"

# Start the workspace
./workspace-setup/scripts/start_workspace.sh

# Run your first audit
python workspace-setup/scripts/audit_workspace.py

• Morning Brief: Get prioritized leads and outreach templates
• Smart Templates: AI-selected email sequences based on prospect profile
• Response Tracking: Real-time alerts when prospects engage

• Deal Intelligence: AI analyzes all customer interactions
• Competitive Alerts: Instant notification of competitor mentions
• Meeting Prep: Auto-generated context documents for every call

• Pipeline Analytics: Real-time pipeline health monitoring
• Team Performance: Individual and team dashboards
• Forecast Accuracy: AI-powered forecast predictions

• Health Monitoring: Automated customer health scoring
• Churn Prevention: Early warning system with action plans
• Expansion Opportunities: AI identifies upsell signals

# Generate context for any customer interaction
context = generate_customer_context(
    customer="acme-corp",
    size="standard",  # 5K, 40K, or 200K+ tokens
    purpose="executive_meeting"
)

• Lead to Close: Enterprise (4-6 months) and SMB (2-8 weeks) workflows
• Trigger Engine: Monitors keywords and patterns across all channels
• Action Automation: Automatically creates tasks and sends notifications

• Customer Context Analyzer: Comprehensive intelligence gathering
• Deal Progression Advisor: Next best action recommendations
• Competitive Intelligence Agent: Real-time competitive analysis
• Report Generator: Automated report creation

• CRM: Salesforce, HubSpot ready
• Communication: Slack, Email, Calendar
• Analytics: Gong, Granola meeting intelligence
• Storage: Local files or cloud storage

Organizations using DealKit report:

• 30% faster sales cycles through intelligent automation
• 25% higher win rates with AI-powered insights
• 50% reduction in admin time via automated reporting
• 2x improvement in forecast accuracy using predictive analytics

{
  "company_name": "Your Company",
  "team_size": 10,
  "sales_methodology": "MEDDPICC",
  "reporting_frequency": "daily",
  "ai_agents": ["customer-analyzer", "deal-advisor"]
}

# Slack integration for real-time intelligence
slack_config = {
    "channels": ["#sales", "#customer-success"],
    "keywords": ["budget approved", "looking for solution"],
    "alert_threshold": "high"
}

• Getting Started Guide - Step-by-step setup
• Architecture Overview - Complete system design
• Command Reference - Common tasks and shortcuts
• Contributing Guide - Development guidelines and governance

We welcome contributions! The workspace is designed to maintain its structure automatically:

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Run the audit before committing (python workspace-setup/scripts/audit_workspace.py)
4. Commit your changes (structure validation runs automatically)
5. Push to the branch (git push origin feature/AmazingFeature)
6. Open a Pull Request

• Follow the established naming conventions (lowercase-hyphenated for folders)
• Maintain separation of concerns (see PROJECT_AUDIT.md)
• Add tests for new agents and integrations
• Update documentation for new features

• All credentials use environment variables
• Customer data stays in isolated directories
• Built-in compliance for GDPR/CCPA
• Audit trails for all actions

• Voice-powered meeting assistant
• Advanced predictive analytics
• Mobile companion app
• Natural language deal updates
• Automated coaching recommendations

• Documentation: Full docs
• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Email: [email protected]

This project is licensed under the MIT License - see the LICENSE file for details.

• Built with insights from 100+ sales professionals
• Powered by Claude AI architecture
• Inspired by modern sales methodologies

Ready to revolutionize your sales process?
⭐ Star us on GitHub • 📖 Get Started • 💬 Get Help

Made with ❤️ by the sales community, for the sales community