📋 NZC LLM Bill Ingestor

A powerful AI-powered solution for automated bill processing and energy consumption tracking in Salesforce Net Zero Cloud

🚀 Quick Deploy

One-click deployment to your Salesforce org

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✨ Features

🤖 AI-Powered Analysis

• Smart Bill Processing: Leverages Einstein AI to automatically extract key information from utility bills
• Multi-Format Support: Processes various file formats including images and PDFs
• Intelligent Data Extraction: Automatically identifies account names, consumption data, and billing periods

🏗️ Salesforce Integration

• Net Zero Cloud Compatible: Seamlessly integrates with Salesforce Net Zero Cloud for sustainability tracking
• Lightning Web Components: Modern, responsive UI built with Lightning Web Components
• Flow Integration: Includes pre-built flows for automated record processing
• Energy Use Record Creation: Automatically creates StnryAssetEnrgyUse records from analyzed data

📊 Energy Management

• Consumption Tracking: Monitors electricity usage across multiple sites
• Historical Data: Maintains comprehensive records of energy consumption patterns
• Multi-Site Support: Handles bills containing data for multiple locations

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🚀 Getting Started

📋 Prerequisites

Before you begin, ensure you have the following:

• ✅ Salesforce Net Zero Cloud licensed and configured
• ✅ Git installed on your local machine
• ✅ Salesforce CLI (latest version recommended)
• ✅ Salesforce user with deployment permissions
• ✅ Active Salesforce org (Sandbox or Developer Edition)
• ✅ Einstein AI features enabled in your org

🔧 Installation

Choose your preferred deployment method:

🎯 Option 1: One-Click GitHub Deploy (Recommended)

Click the "Deploy to Salesforce" button above for instant deployment to your org.

📦 Option 2: Workbench Deployment

For environments where GitHub access is restricted:

1. Download the pre-built deployment package: NZC-LLM-Bill-Ingestor-Deploy.zip
2. Navigate to Salesforce Workbench
3. Login to your target org
4. Go to Migration → Deploy
5. Upload the zip file and deploy

🛠️ Option 3: Salesforce CLI Deployment

For developers who prefer command-line tools:

3.1 Clone the Repository

git clone https://github.com/jvillalpando_sfemu/NZC-LLM-Bill-Ingestor.git
cd NZC-LLM-Bill-Ingestor

3.2 Authorize Your Org

# For sandbox/production orgs
sfdx auth:web:login --setalias MyOrg --instanceurl https://test.salesforce.com

# For developer orgs
sfdx auth:web:login --setalias MyOrg

3.3 Deploy the Metadata

# Deploy all components
sfdx force:source:deploy -p force-app -u MyOrg

# Or use CumulusCI (if configured)
cci flow run dev_org --org dev

⚡ Post-Deployment Configuration

After deploying with any method above, ensure your org has:

• ✅ Einstein AI Platform enabled
• ✅ Prompt Template Builder access
• ✅ Required Einstein credits available
• ✅ Net Zero Cloud licensed and configured

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🎯 Usage

📱 Adding Components to Lightning Pages

1. Navigate to your target Lightning Page (Home, Account, etc.)
2. Edit the page using the Lightning App Builder
3. Find the Image Analyzer component in the Custom Components section
4. Drag the component to your desired location
5. Configure component properties as needed
6. Save and Activate the page

🔄 Processing Bills

1. Upload a bill file using the Image Analyzer component
2. Click "Analyze with AI" to process the document
3. Review the extracted data in the results panel
4. Click "Create Energy Records" to automatically create StnryAssetEnrgyUse records
5. Monitor the progress and view created record links

📊 Viewing Results

• Energy records are automatically linked to your parent record
• View created records by clicking the provided links
• Track consumption patterns in Net Zero Cloud dashboards

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🏗️ Architecture

graph TB
    A[Lightning Web Component] --> B[AIFileAnalysisController]
    B --> C[Einstein AI Prompt Templates]
    B --> D[MultipleJSONParser]
    B --> E[StnryAssetEnrgyUse Records]
    C --> F[AI Analysis Results]
    F --> G[JSON Parser]
    G --> E
    E --> H[Net Zero Cloud]

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🧩 Key Components

Component	Description
imageAnalyzer	Lightning Web Component for file upload and AI analysis
AIFileAnalysisController	Apex controller handling AI processing and record creation
MultipleJSONParser	Utility class for parsing complex JSON structures
Process_AI_Analysis_Result	Flow for additional processing workflows

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🤝 Contributing

We welcome contributions to improve the NZC LLM Bill Ingestor! Please follow these steps:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📝 Development Guidelines

• Follow Salesforce coding standards
• Include comprehensive test coverage (>75%)
• Update documentation for new features
• Test thoroughly in multiple org types

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📄 License

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

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🆘 Support

• 📚 Documentation: Check our Wiki for detailed guides
• 🐛 Issues: Report bugs via GitHub Issues
• 💬 Discussions: Join the conversation in GitHub Discussions
• 📧 Contact: Reach out to the maintainers for enterprise support

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Made with ❤️ for the Salesforce Community

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