Common Use Cases

Huf agents can automate a wide variety of tasks across your Frappe system. Here are common use cases to inspire your own implementations.

Customer Support Automation

Problem: Support team spends too much time on repetitive questions and ticket routing.

Solution: AI agent handles common inquiries, routes complex issues, and provides instant responses.

Capabilities

Answer FAQs: Common questions about products, services, policies
Ticket Routing: Analyze tickets and assign to correct team
Information Lookup: Retrieve customer history, order status, account details
Escalation: Identify urgent issues and escalate appropriately
Follow-up: Schedule follow-ups and reminders

Agent Configuration

Tools Needed:

Get Document (Customer, Support Ticket)
Get List (Support Ticket with filters)
Create Document (Support Ticket)
Update Document (Support Ticket)
HTTP Request (for Slack/Email notifications)

Example Instructions:


You are a customer support assistant. Your role is to:
1. Answer common questions about products, orders, and policies
2. Look up customer information when requested
3. Create support tickets for issues you cannot resolve
4. Route tickets to appropriate teams based on issue type
5. Escalate urgent issues immediately

Always be polite, professional, and helpful. If you don't know 
something, create a support ticket and let the user know.

Benefits

24/7 Availability: Instant responses anytime
Faster Resolution: Common issues resolved immediately
Better Routing: Tickets go to right team first time
Consistent Quality: Same high-quality responses every time
Team Focus: Human agents handle complex cases

Document Automation

Problem: Manual document processing is slow, error-prone, and doesn’t scale.

Solution: Agents validate, enrich, and route documents automatically.

Capabilities

Form Validation: Check required fields, formats, business rules
Data Enrichment: Look up and add missing information
Auto-routing: Send documents to correct approvers/workflows
Duplicate Detection: Identify and flag duplicate entries
Auto-correction: Fix common errors automatically

Agent Configuration

Tools Needed:

Get Document (various DocTypes)
Get List (for duplicate checking)
Create Document (for related records)
Update Document (for corrections)
Submit Document (for approvals)

Example: Invoice Validation Agent

Instructions:


You are an invoice validation agent. When invoices are submitted:
1. Verify pricing matches current price list
2. Check customer credit limit
3. Validate tax calculations
4. Ensure all required fields are filled
5. Check for duplicate invoices

If validation passes, add a comment confirming validation.
If issues are found, add comments with specific problems and 
notify the accounts team.

Trigger: On Submit of Sales Invoice DocType

Benefits

Faster Processing: Instant validation vs manual review
Error Reduction: Catch issues before submission
Consistency: Same rules applied every time
Audit Trail: All validations logged
Scalability: Handle any volume

Data Processing Workflows

Problem: Data needs to be transformed, calculated, or aggregated across multiple sources.

Solution: Agents process data, perform calculations, and generate reports automatically.

Capabilities

Data Aggregation: Combine data from multiple sources
Calculations: Perform complex calculations and formulas
Data Transformation: Convert formats, normalize data
Report Generation: Create summaries and analytics
Data Synchronization: Keep related records in sync

Agent Configuration

Tools Needed:

Get List (for data retrieval)
Get Document (for details)
Create Document (for reports)
Custom Tools (for calculations)
HTTP Request (for external data)

Example: Sales Report Generator

Instructions:


Generate daily sales reports by:
1. Retrieving all sales invoices from today
2. Calculating totals by customer, product, and region
3. Comparing to previous day and week
4. Identifying top performers and trends
5. Creating a summary document
6. Sending report via email to sales team

Format the report clearly with sections for:
- Overall summary
- Top customers
- Top products
- Regional breakdown
- Trends and insights

Trigger: Scheduled (Daily at 9 AM)

Benefits

Time Savings: Automated report generation
Accuracy: No manual calculation errors
Consistency: Same format every time
Timeliness: Reports ready when needed
Insights: AI can identify patterns and trends

Smart Notifications

Problem: Important events happen but stakeholders aren’t notified promptly or appropriately.

Solution: Agents monitor events and send intelligent, contextual notifications.

Capabilities

Event Monitoring: Watch for specific document changes
Contextual Alerts: Include relevant information in notifications
Multi-channel: Send via Slack, Email, SMS, etc.
Smart Filtering: Only notify when conditions are met
Escalation: Escalate if no response received

Agent Configuration

Tools Needed:

Get Document (for context)
Get List (for related records)
HTTP Request (for Slack/Email/SMS)
Custom Tools (for notification logic)

Example: High-Priority Ticket Alert

Instructions:


When a high-priority support ticket is created:
1. Retrieve ticket details
2. Check customer information and history
3. Determine appropriate team based on issue type
4. Format notification with:
   - Ticket ID and subject
   - Customer name and tier
   - Issue description
   - Suggested assignee
5. Send to relevant Slack channel
6. Also email the team lead if customer is VIP

Only send notifications for tickets marked "High" or "Critical" priority.

Trigger: After Insert on Support Ticket (with condition: priority = “High”)

Benefits

Immediate Alerts: Instant notification of important events
Context Rich: Include relevant information automatically
Right Audience: Notify correct people based on context
Reduced Noise: Only notify when necessary
Multi-channel: Reach people where they are

Lead Management and Qualification

Problem: Leads come in but aren’t qualified, scored, or assigned efficiently.

Solution: Agents analyze leads, score them, and route to appropriate sales reps.

Capabilities

Lead Scoring: Evaluate leads based on multiple criteria
Data Enrichment: Look up company info, social profiles
Assignment Logic: Assign to best sales rep based on territory, workload, expertise
Follow-up Scheduling: Set appropriate follow-up dates
Qualification: Determine if lead meets criteria

Agent Configuration

Tools Needed:

Get Document (Lead, Customer, Territory)
Get List (Sales Person, existing leads)
Create Document (Lead, Task)
Update Document (Lead assignment)
Custom Tools (for scoring algorithm)

Example: Lead Qualifier Agent

Instructions:


When a new lead is created:
1. Score the lead based on:
   - Company size (from company_name lookup)
   - Industry match with our ideal customer profile
   - Source quality (referral > website > cold)
   - Budget indicators in description
2. Assign to sales rep based on:
   - Territory match
   - Current workload (fewer active leads = higher priority)
   - Industry expertise
3. Set follow-up date:
   - Hot leads: Same day
   - Warm leads: Next business day
   - Cold leads: Next week
4. Add internal notes with scoring rationale
5. Notify assigned sales rep

Trigger: After Insert on Lead DocType

Benefits

Faster Response: Hot leads get immediate attention
Better Assignment: Leads go to right rep automatically
Consistent Scoring: Same criteria applied to all leads
Higher Conversion: Better qualification = better close rates
Time Savings: Sales reps focus on qualified leads

Report Generation from Natural Language

Problem: Users need reports but don’t know how to create them or use complex report builders.

Solution: Agents understand natural language requests and generate reports automatically.

Capabilities

Natural Language Understanding: Parse user requests like “Show me sales this month”
Query Building: Convert requests to database queries
Data Retrieval: Fetch relevant data
Formatting: Present data in readable format
Visualization: Suggest charts or graphs when appropriate

Agent Configuration

Tools Needed:

Get List (with dynamic filters)
Get Document (for details)
Custom Tools (for report formatting)
HTTP Request (for exporting to Excel/PDF)

Example: Report Generator Agent

Instructions:


You are a report generation assistant. Users ask for reports in 
natural language, and you create them.

When users request reports:
1. Understand what data they want (sales, inventory, customers, etc.)
2. Determine time period (today, this week, this month, custom range)
3. Identify filters (by customer, product, region, etc.)
4. Retrieve the data using appropriate tools
5. Format results clearly:
   - Summary statistics
   - Detailed breakdown
   - Comparisons if requested
6. Offer to export to Excel or PDF if needed

Be conversational and ask clarifying questions if the request 
is ambiguous.

Tools:

get_list (for data retrieval)
generate_report (custom tool for formatting)
export_to_excel (custom tool)

Benefits

Accessibility: Non-technical users can get reports
Speed: Instant report generation
Flexibility: Handle varied requests
Natural Interaction: Users ask naturally, not query syntax
Time Savings: No need to build reports manually

Additional Use Cases

Inventory Management

Stock Monitoring: Alert when items below reorder level
Demand Forecasting: Predict future demand based on history
Purchase Suggestions: Recommend what to order and when
Warehouse Optimization: Suggest optimal warehouse allocation

Financial Operations

Invoice Validation: Check invoices before payment
Payment Matching: Match payments to invoices automatically
Budget Monitoring: Track spending against budgets
Expense Categorization: Automatically categorize expenses

HR Automation

Resume Screening: Analyze resumes and score candidates
Leave Balance Tracking: Monitor and report leave balances
Performance Summaries: Generate performance review summaries
Onboarding Automation: Guide new employees through onboarding

Sales Operations

Opportunity Scoring: Score sales opportunities
Quote Generation: Create quotes from requirements
Contract Review: Review contracts for key terms
Pipeline Management: Update pipeline based on activities

Operations

Quality Control: Validate production quality
Maintenance Scheduling: Schedule equipment maintenance
Compliance Checking: Verify regulatory compliance
Documentation: Auto-generate process documentation

Choosing the Right Use Case

Start Simple

Good First Use Cases:

FAQ automation
Simple data lookups
Basic validation
Notification sending

Why: Low risk, high value, easy to test

Build Complexity

Intermediate Use Cases:

Multi-step workflows
Data processing
Report generation
Conditional routing

Why: More value, requires planning

Advanced Automation

Complex Use Cases:

Multi-agent workflows
Complex decision trees
Integration-heavy
Real-time processing

Why: Maximum value, requires expertise

Implementation Tips

1. Start with One Use Case

Don’t try to automate everything at once:

Pick one high-value use case
Build and test thoroughly
Iterate based on feedback
Expand to other use cases

2. Define Success Metrics

Measure impact:

Time saved
Error reduction
Response time improvement
User satisfaction

3. Involve End Users

Get input from people who will use it:

Understand their workflow
Get feedback on agent behavior
Iterate based on real usage
Train users on how to interact

4. Monitor and Improve

Continuously optimize:

Review Agent Run logs
Identify failure patterns
Refine instructions
Add missing tools
Improve prompts

5. Document Everything

Keep records of:

Use case requirements
Agent configuration
Tool assignments
Success metrics
Lessons learned

What’s Next?

Example Agents - See complete agent configurations
Creating Agents - Learn how to build agents
Tools - Understand available tools
Triggers - Automate agent execution

Have a use case idea? Share it in GitHub discussions !