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Use Cases

Objective:

Develop an AI voice agent that automates customer verification, EMI reminders, payment collection, and payment plans and remind customer about outstanding payment, record their response (Paid/Promise to Pay/Dispute) and escalate if needed.

Step-By-Step Use Case:

Scenario 1. Customer Verification

  • Trigger Event: The AI voice agent calls the customer, who has taken out a consumer loan.
  • Action:
    • The AI asks, "Hello, this is [Company Name]. Are we speaking with [Customer's Full Name]?"
    • If the customer confirms the identity, the conversation continues.
    • If the customer does not confirm, the agent will ask for a specific piece of information (e.g., date of birth or last four digits of their social security number or loan number) to verify their identity.
  • Outcome:
    • If the customer is verified successfully, the agent proceeds to the next step.
    • If verification fails, the AI agent will prompt the user with a polite message and end the call with a request to contact customer service.

Scenario 2. EMI Reminder

  • Trigger Event: After successful verification, the AI agent proceeds with a reminder call.
  • Action:
    • The AI says: “I am calling to remind you about your upcoming EMI payment for your loan with [Company Name]. Your next EMI is due on [Due Date]. The amount is [Amount].”
    • It will also mention any other details relevant to the payment, such as the loan term or previous payments made.
  • Outcome:
    • The customer is informed about the due EMI and its due date.

Scenario 3. Payment Collection

  • Trigger Event:Trigger Event: After the reminder, the AI agent asks the customer if they are ready to make a payment.
  • Action:
    • If the customer says, “Yes,” the AI will ask for the payment method, e.g., credit card, debit card, or other available methods.
    • The agent will then share a secure payment link over the phone or text message, depending on what communication method is available.
    • The AI will say, “To make the payment now, please follow this link: [Link].”
  • Outcome:
    • Customer is provided with a payment option and a direct link to pay.

Scenario 4. Payment at a Later Date (Post-Due Date)

  • Trigger Event: If the customer wants to pay after the due date or requests a later date to pay..
  • Action:
    • The AI will notify the customer of the following: “Please be aware that if you pay after the due date, there will be a late fee of [Late Fee] and interest charges of [Interest Charges] on your outstanding balance.”
    • The AI will then provide the customer with a payment link and offer to set up a plan if the customer is unable to pay the full amount.
  • Outcome:
    • Customer is informed about the consequences of paying after the due date, including late fees and interest charges.

Scenario 5. Payment Plan Setup

  • Trigger Event: If the customer requests a payment plan, either because they cannot pay in full or they have promised to pay at a later date.
  • Action:
    • The AI asks: “Would you like to set up a payment plan to help with your outstanding balance?”
    • If the customer agrees, the AI will gather details like how much they can pay monthly or at a specific date.
    • The AI will confirm the payment plan: “Your payment plan will be set at [Amount] per month starting from [Start Date], and the final payment will be on [End Date].”
    • The AI will ask for confirmation from the customer.
  • Outcome:
    • The payment plan is set up, and the customer is informed of the agreed-upon schedule.

Scenario 6. Reminders for Payment Plan

  • Trigger Event:The payment plan is active, and future reminders are necessary.
  • Action:
    • The AI will call the customer ahead of the due date for each installment, saying: “This is a reminder that your payment of [Amount] is due on [Date].
    • The AI will also mention any outstanding balances and notify the customer if there are any issues with the payment plan.
  • Outcome:
    • The customer receives timely reminders for payments.

Scenario 7. Handling Payment Issues

  • Trigger Event: If a payment fails, or the customer requests assistance in case of financial issues.
  • Action:
    • The AI will inform the customer of the failed transaction and ask: “Your last payment of [Amount] did not go through. Would you like assistance with making the payment again or rescheduling it?”
    • If needed, the AI may offer to set up a revised payment plan or connect the customer with a human representative if more support is required.
  • Outcome:
    • The customer receives support in resolving payment issues, either through rescheduling or by offering alternatives.

Scenario 8. Payment Confirmation

  • Trigger Event:The customer successfully makes a payment.
  • Action:
    • The AI will confirm: “Thank you for your payment of [Amount]. Your loan balance is now [Remaining Balance], and your next due date is [Next Due Date].”
    • The agent will also confirm any late fees or interest charges, if applicable.
  • Outcome:
    • Customer receives confirmation and updated balance details.

Scenario 9. Ending the Call

  • Trigger Event:The transaction is complete, or the payment plan is set.
  • Action:
    • The AI will wrap up the conversation by saying: “Thank you for your time. If you have any questions or need further assistance, please don’t hesitate to contact us at [Customer Service Number/Website].”
    • The call will be ended professionally and politely.
  • Outcome:
    • The call concludes with all relevant information shared, and the customer is left with the necessary resources for follow-up.

Additional Features & Considerations:

  • Multi-Language Support: The AI voice agent should be capable of handling multiple languages, based on customer preferences.
  • Security: All sensitive information (payment details, verification information) should be handled securely with encryption and PCI compliance.
  • Escalation Protocol: If at any point, the customer requests to speak to a human agent, the AI should be able to escalate the call smoothly.
  • Automated Reporting: The AI should generate a log of all interactions for internal use, including customer verification details, payments made, payment plans set, and issues encountered.
  • Error Handling: If the AI cannot understand the customer, it should politely ask for clarification or offer alternative ways to resolve issues

Reward Criteria for the Hackathon:

  • Functionality: The AI agent should handle all outlined tasks efficiently, including verification, reminders, payment processing, and late fee management.
  • User Experience: The agent should be easy to interact with, providing clear instructions and options to the customer.
  • Security and Privacy: Ensuring that customer data and transactions are securely handled.
  • Innovation: Creative ways of improving the process, like using NLP techniques for better conversation flow or optimizing payment processing steps.

Objective:

Build voice-based AI agents that can assist users with searching real estate properties and scheduling appointments with agents, call back later if requested and propose site visits. simulate data using MagicBrick/ 99Acre APIs etc.

Scenario 1: Initial Property Inquiry Call

The AI agent calls the user (or answers an incoming call) and asks:
  • What type of property are you looking for? (e.g., apartment, villa, commercial space)
  • Preferred location?
  • Budget range?
  • Any specific requirements? (e.g., number of bedrooms, parking, pet-friendly)

Scenario 2: Suggesting Matching Properties

The AI agent calls the user (or answers an incoming call) and asks:
  • Shortlists and suggests 2-3 matching properties
  • Shares brief details on each (location, price, size, features)
  • Asks which one(s) the user would like more information about or visit

Scenario 3: Appointment Scheduling

Once the user shows interest:
  • Once the user shows interest:
  • Confirms a date & time that works for the user
  • Optionally books the calendar and sends confirmation via SMS/email

Scenario 4: Appointment Reminder and Reconfirmation (Day Before or Same Day)

  • Calls the user to remind them of the upcoming appointment
  • Asks if they are still available or if they want to reschedule
  • Updates the schedule accordingly and confirms again

Scenario 5: Follow-Up Call After Site Visit

The AI follows up:
  • Asks for feedback on the property visit
  • Checks if the user is interested in proceeding or would like to explore other options
  • BuChecks if the user is interested in proceeding or would like to explore other optionsdg

Scenario 6 : Handling Missed Calls or No Shows In case of a missed appointment:

  • AI calls to apologize and reschedule
  • Offers alternate timings
  • Optionally asks for the reason to improve future planning

Scenario 7 : Handling Cold Leads / Lead Revival For older leads that went cold:

  • AI reaches out and asks if the user is still interested in buying/renting
  • Offers new properties that match market trends or deals
  • Reinitiates the appointment funnel

Objective:

AI Voice agent must call leads, confirm basic info (e.g., name, service interest), propose available slots, book appointment in system

Scenario 1: Cold Outreach Introduction

Objective:

Test basic conversation skills and clarity in introducing the product.

Context:

The AI agent is initiating a conversation with a prospect who has never heard of the SaaS product.

Expected Capabilities:
  • Brief, engaging self-introduction
  • Clear value proposition
  • Ask relevant qualifying questions (e.g., role, industry, needs)
  • Capture lead’s name and email

Scenario 2: Website Chatbot for Product Discovery

Objective:

Simulate real-time web chat experience for inbound interest.

Context:

A visitor lands on the website. The AI initiates a conversation to guide them.

Expected Capabilities:
  • Greet visitor and identify their goals
  • Recommend relevant product features
  • Offer demo scheduling or resource download
  • Handle FAQs (pricing, integrations, support)

Scenario 3: Objection Handling

Objective:

Test AI’s ability to maintain engagement and counter hesitations.

Context:

The AI agent is initiating a conversation with a prospect who has never heard of the SaaS product.

Expected Capabilities:
  • Empathetic response to objections
  • Clarify misunderstandings
  • Offer comparative advantages or testimonials
  • Guide toward a CTA (e.g., free trial, demo)

Scenario 4: Qualification Conversation

Objective:

Qualify the lead based on specific criteria (BANT, CHAMP, etc.).

Context:

The prospect shows interest, and the agent must gather data for sales team handoff.

Expected Capabilities:
  • Ask strategic questions: budget, authority, timeline, etc.
  • Categorize lead as hot/warm/cold
  • ORecord lead details in CRM-ready format
  • Ask permission to pass details to human sales rep.

Scenario 5: Follow-up & Nurture Flow

Objective:

Show continuity and memory retention across multiple sessions.

Context:

The prospect has interacted before but didn’t convert. AI needs to re-engage.

Expected Capabilities:
  • Recall past interaction
  • Provide new offer (e.g., webinar, case study)
  • Use urgency (limited-time discount, feature update)
  • Escalate to human if qualified

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