📋 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

Note: If you encounter authentication issues, you may need to authorize the GitHub Salesforce Deploy Tool to access the salesforce-misc organization. Alternatively, use the Salesforce CLI deployment method below.

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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
• 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 (Setup > Einstein Setup > Enable Turn on Einstein, if it's not already turned on)

🔧 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:
   • Direct download: NZC-LLM-Bill-Ingestor-Deploy.zip
   • Or download from the GitHub Releases tab
2. Navigate to Salesforce Workbench
3. Login to your target org
4. Go to Migration → Deploy
5. Upload the zip file and deploy

Alternative Tools: You can also deploy using Salesforce Inspector or the Ant Migration Tool.

🛠️ Option 3: Salesforce CLI Deployment

For developers who prefer command-line tools:

3.1 Clone the Repository

git clone https://github.com/salesforce-misc/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 (Salesforce CLI v2)
sf project deploy start --source-dir force-app --target-org MyOrg

# Or using legacy sfdx command
sfdx force:source:deploy -p force-app -u MyOrg

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

Note: This accelerator is compatible with CI/CD tools like Gearset, Copado, and Flosum.

⚡ Post-Deployment Configuration

After deploying with any method above, complete these manual steps:

1. Enable Einstein AI Platform

   • Navigate to Setup → Einstein Setup
   • Toggle on Turn on Einstein if not already enabled

2. Access Prompt Template Builder

   • Ensure you have access to Prompt Template Builder (Setup > Einstein Generative AI > Prompt Builder)
   • Verify the Analyze_Files prompt template is active

3. Verify Einstein Credits

   • Check that you have sufficient Einstein credits available (check Digital Wallet App, see here for required permissions)
   • Credits are consumed per AI analysis request

4. Configure Net Zero Cloud

   • Ensure Net Zero Cloud is licensed and configured
   • Verify StnryAssetEnrgyUse object is available

5. Add Component to Lightning Pages

   • Follow the Usage instructions below to add the component to your pages

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🎯 Usage

📱 Adding Components to Lightning Pages

1. Navigate to the Stationary Asset Environmental Source Object Lightning Page
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. 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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🏗️ Technical Architecture

This accelerator contains the following metadata:

• 2 Lightning Web Components (imageAnalyzer, energyRecordDetail)
• 2 Apex Classes (AIFileAnalysisController, MultipleJSONParser)
• 1 Einstein AI Prompt Template (Analyze_Files)

Architecture Diagram

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

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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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🐛 How to Report Bugs

Found a bug or have a feature request? Please report it via GitHub Issues.

When reporting bugs, please include:

• Steps to reproduce the issue
• Expected vs. actual behavior
• Salesforce org version and edition
• Screenshots or error messages (if applicable)

🆘 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

⚠️ Disclaimer

This accelerator is open-source, not an official Salesforce product, and is community-supported. Salesforce does not provide official support for this accelerator. Use at your own risk and test thoroughly in a sandbox environment before deploying to production.

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Made with ❤️ for the Salesforce Community

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