Transform your ERPNext project management with AI-powered task automation, dynamic template systems, and intelligent lead-to-project conversion workflows.
# Install TaskFlow AI in your ERPNext instance
bench get-app https://github.com/yourusername/taskflow_ai.git
bench --site your-site-name install-app taskflow_ai
bench --site your-site-name migrate- Smart Task Assignment: AI recommends optimal team members based on skills, workload, and performance
- Intelligent Duration Prediction: Machine learning models predict realistic task completion times
- Employee Skill Matching: Advanced skill profiling system for precise task assignments
- Workload Optimization: Automatic workload balancing across team members
- Task Template Groups: Organize templates into logical groups for different project types
- Dynamic Relationships: Link templates to groups with flexible sequence management
- Project Generation: Create complete projects from template groups with one click
- Customizable Workflows: Adapt templates for your specific business processes
- Project Planning Workflow: Manual control over lead-to-project conversion
- Review & Approval Process: Structured approval workflow for project managers
- Lead Intelligence: Advanced lead segmentation and scoring system
- Automated Data Population: Smart form filling from lead information
- Performance Insights: Track team performance, task completion rates, and project success
- Skill Analytics: Monitor skill development and identify training needs
- Project Forecasting: Predict project timelines and resource requirements
- Department Intelligence: Optimize departmental workflows and assignments
### Core Components
#### 1. AI Task Assignment System
- **AI Task Profile**: Define skill requirements and complexity levels
- **Employee Skills**: Comprehensive skill profiling with experience levels
- **Smart Matching Algorithm**: ML-powered assignment recommendations
- **Performance Feedback Loop**: Continuous learning from assignment outcomes
#### 2. Dynamic Template Management
- **Task Templates**: Reusable task definitions with metadata
- **Template Groups**: Logical grouping of related templates
- **Sequence Management**: Flexible ordering within template groups
- **Project Generation**: Automated project creation from templates
#### 3. Enhanced Project Planning
- **Project Planning DocType**: Comprehensive planning document
- **Approval Workflow**: Draft → Under Review → Approved → Submitted
- **Lead Integration**: Seamless conversion from leads to planned projects
- **Timeline Estimation**: Automatic scheduling based on template data
### Technical Stack
- **Backend**: Python with Frappe Framework
- **Frontend**: JavaScript with Frappe's UI components
- **Database**: MariaDB with optimized queries
- **AI/ML**: Scikit-learn for assignment algorithms
- **Integration**: Deep ERPNext integration
## 📚 Usage Guide
### Setting Up Task Templates
1. **Create Task Templates**
Navigate to: Task Template > New
- Define task details, duration, and requirements
- Set skill requirements and complexity
- Add to appropriate template groups
2. **Configure Template Groups**
Navigate to: Task Template Group > New
- Create logical groupings (e.g., "Website Development", "ERP Implementation")
- Templates can be dynamically added/removed from groups
### Lead to Project Conversion
1. **Enhanced Lead Management**
- Leads automatically create Project Planning documents
- Manual review and approval process
- Rich planning interface with budget and timeline
2. **Project Creation**
- Select template group for project type
- System generates complete project structure
- Tasks automatically assigned based on skills
### AI Task Assignment
1. **Configure Employee Skills**
Navigate to: Employee > Skills Tab
- Add relevant skills with proficiency levels
- System learns from assignment feedback
2. **Set Up AI Task Profiles**
Navigate to: AI Task Profile > New
- Define skill requirements for task types
- Set complexity and priority levels
## 🔧 Configuration
### Required Setup
1. **Employee Skills Configuration**
- Configure employee skill profiles
- Set proficiency levels (Beginner, Intermediate, Advanced, Expert)
- Regular skill assessment and updates
2. **Department Intelligence**
- Set up department-specific workflows
- Configure department lead assignments
- Optimize departmental task distribution
3. **Lead Segment System**
- Configure lead scoring criteria
- Set up segment-based routing
- Automate lead qualification process
### Optional Enhancements
1. **Custom Task Categories**
- Define business-specific task types
- Create custom skill requirements
- Set up industry-specific templates
2. **Performance Analytics**
- Configure KPI tracking
- Set up automated reporting
- Enable performance dashboards
## 🚀 Advanced Features
### Machine Learning Capabilities
- **Predictive Task Duration**: ML models learn from historical data
- **Assignment Optimization**: AI considers multiple factors for optimal assignments
- **Performance Prediction**: Forecast project success probability
- **Risk Assessment**: Identify potential bottlenecks and risks
### Integration Points
- **CRM Integration**: Seamless lead management workflow
- **HR Integration**: Employee skill and performance tracking
- **Project Management**: Complete project lifecycle management
- **Reporting**: Advanced analytics and business intelligence
### API Endpoints
```python
# Get AI task assignment recommendations
taskflow_ai.api.get_task_assignment_recommendations(task_id, filters)
# Generate project from template group
taskflow_ai.api.create_project_from_template_group(planning_id, group_name)
# Get employee skill analysis
taskflow_ai.api.get_employee_skill_analysis(employee_id)
# Validate lead conversion eligibility
taskflow_ai.api.validate_lead_conversion_eligibility(lead_id)
-
Assignment Algorithm Not Working
- Verify employee skills are properly configured
- Check AI Task Profile requirements
- Ensure sufficient employee pool for assignment
-
Template Group Issues
- Verify template group relationships
- Check template sequence ordering
- Validate template completeness
-
Lead Conversion Problems
- Check lead status and qualification
- Verify project planning workflow
- Ensure proper permissions
# Enable detailed logging
bench --site your-site-name set-config developer_mode 1
# Check system status
bench --site your-site-name execute taskflow_ai.api.system_monitor.quick_system_check- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
This project is licensed under the MIT License - see the LICENSE file for details.
- Documentation: Full Documentation
- Issues: GitHub Issues
- Discussions: GitHub Discussions
- Built on the powerful Frappe Framework
- Integrates seamlessly with ERPNext
- Inspired by modern AI-driven project management methodologies
Made with ❤️ for the ERPNext Community
### Workflow Overview
```mermaid
graph TD
A[Salesperson creates Lead] --> B[Lead status → Interested]
B --> C[AI triggers project generation]
C --> D[Select template: ERPNext Implementation]
D --> E[AI generates task hierarchy]
E --> F[Predict durations & risks]
F --> G[Recommend assignees]
G --> H[Build optimized schedule]
H --> I[Team review & approval]
I --> J[Execute & learn]
- Frappe Framework v15+
- ERPNext v15+
- Python 3.8+
# 1. Get the app
cd ~/frappe-bench/apps
git clone https://github.com/your-repo/taskflow_ai.git
# 2. Install in your site
bench --site your-site.local install-app taskflow_ai
# 3. Run the setup script
./apps/taskflow_ai/install.sh your-site.local# Install app
bench --site your-site.local install-app taskflow_ai
# Run migrations
bench --site your-site.local migrate
# Install sample templates
bench --site your-site.local execute taskflow_ai.install_templates.install_sample_templatesNavigate to TaskFlow AI > Task Template to see the pre-installed ERPNext implementation workflow:
- Pre-Sales: Discovery call, requirements gathering, demo, proposal
- Implementation: Kickoff, system setup, module configurations
- Customization: Gap analysis, custom development, workflows, reports
- Go-Live: Training, UAT, data migration, hypercare support
- Create a new Lead in ERPNext
- Set status to "Interested"
- System will prompt: "Generate AI project for this lead?"
- Select template group and confirm
- Watch as AI creates complete project with intelligent task assignments!
Open any generated task to see:
- Predicted Duration: 12.5h (P80: 15h)
- Risk Assessment: 25% slip probability
- Top Assignees: Ranked by fit score with reasoning
- Confidence Score: 82% prediction confidence
Create custom templates for your specific services:
# Example: Custom API Integration Template
template = {
"template_name": "Third-party API Integration",
"category": "Customization",
"default_duration_hours": 16,
"ai_complexity_score": 0.8,
"required_skills": [
{"skill": "Python Development", "required_level": "4"},
{"skill": "API Integration", "required_level": "5"}
]
}Define skills and levels for accurate AI assignments:
- Go to HR > Employee
- Add skills with proficiency levels (1-5)
- AI will use this for optimal task assignments
Configure auto-trigger conditions:
# Lead status triggers
"Lead.status == 'Interested'"
# Opportunity triggers
"Opportunity.status == 'Quotation'"# GET /api/method/taskflow_ai.api.get_task_ai_recommendations
{
"task_name": "TASK-001"
}# POST /api/method/taskflow_ai.api.create_project_from_template
{
"template_group": "ERPNext Implementation",
"project_name": "ABC Corp Implementation",
"customer": "ABC Corporation"
}# GET /api/method/taskflow_ai.api.get_dashboard_data
# Returns: project counts, accuracy metrics, risk analysis# hooks.py
doc_events = {
"Lead": {
"on_update": "taskflow_ai.ai.automation.on_lead_update"
},
"Task": {
"after_insert": "taskflow_ai.ai.pipeline.on_task_created"
}
}Our default template includes 21 tasks across 4 phases:
- Initial Discovery Call (2h)
- Requirements Gathering (8h)
- Product Demo (4h)
- Proposal Creation (6h)
- Project Kickoff (2h)
- Instance Setup (4h)
- CRM Configuration (8h)
- Accounts Setup (12h)
- Inventory Management (10h)
- HR & Payroll (14h)
- Manufacturing Module (16h)
- Gap Analysis (6h)
- Custom Fields/DocTypes (12h)
- Workflow Automation (16h)
- Reports & Dashboards (10h)
- API Integrations (20h)
- User Training (16h)
- UAT Execution (24h)
- Data Migration (20h)
- Go-Live Support (32h)
- Post-Live Hypercare (24h)
Total Estimated Duration: 252 hours (~6-8 weeks)
- Model: LightGBM Regressor
- Features: Task complexity, assignee skills, project context, historical data
- Accuracy Target: <15% Mean Absolute Error
- Output: Duration estimate + confidence intervals (P50, P80, P95)
- Model: XGBoost Classifier
- Output: Slip probability (0-100%)
- Factors: Dependencies, workload, timeline pressure, complexity
- Model: Learning-to-Rank (LambdaMART)
- Ranking Factors: Skill match, availability, performance history, workload
- Output: Ranked list with fit scores and reasoning
- Training Frequency: Weekly automatic retraining
- Feedback Integration: User ratings improve recommendations
- Performance Monitoring: Drift detection and accuracy tracking
- Prediction Accuracy: Target <15% MAE on duration estimates
- On-time Delivery: >85% of tasks completed by predicted date
- Resource Utilization: 75-85% optimal range
- Schedule Conflicts: <10% requiring manual intervention
- Project Setup Time: 2 days → 30 minutes (95% reduction)
- Delivery Predictability: Improved customer satisfaction
- Team Satisfaction: Balanced workloads, reduced overtime
- Revenue Impact: Faster project starts, better resource planning
- Role-based Access: Predictions visible based on user permissions
- Data Anonymization: Training data can be anonymized for privacy
- Audit Trail: All AI decisions are logged and traceable
- GDPR Compliance: Personal data handling follows regulations
We welcome contributions! Please see CONTRIBUTING.md for guidelines.
# Clone and setup development environment
git clone https://github.com/your-repo/taskflow_ai.git
cd taskflow_ai
# Install in development mode
bench get-app --branch develop https://github.com/your-repo/taskflow_ai.git# Run tests
bench --site test-site run-tests --app taskflow_aiThis project is licensed under the MIT License - see the LICENSE file for details.
- Documentation: Wiki
- Issues: GitHub Issues
- Discussions: GitHub Discussions
- Email: sammish.thundiyil@gmail.com
- Advanced ML Models: Deep learning for better predictions
- NLP Integration: Auto-generate tasks from requirement documents
- Mobile App: TaskFlow AI mobile companion
- Integrations: Slack, Teams, Jira connectors
- Advanced Analytics: Predictive project health dashboards
Transform your ERPNext projects with AI. Stop counting hours, start delivering outcomes. 🎯🤖
Built with ❤️ for the ERPNext community
You can install this app using the bench CLI:
cd $PATH_TO_YOUR_BENCH
bench get-app $URL_OF_THIS_REPO --branch develop
bench install-app taskflow_aiThis app uses pre-commit for code formatting and linting. Please install pre-commit and enable it for this repository:
cd apps/taskflow_ai
pre-commit installPre-commit is configured to use the following tools for checking and formatting your code:
- ruff
- eslint
- prettier
- pyupgrade
This app can use GitHub Actions for CI. The following workflows are configured:
- CI: Installs this app and runs unit tests on every push to
developbranch. - Linters: Runs Frappe Semgrep Rules and pip-audit on every pull request.
mit