AgentHack submission type
Enterprise Agents
Name
Sushil Pokhriyal
Team members
How many agents do you use
Multiple agents
Industry category in which use case would best fit in (Select up to 2 industries)
Customer service
Complexity level
Intermediate
Summary (abstract)
Customer disputes or complaints often arise when individuals are frustrated by service failures, defective products, billing inaccuracies, or unexpected delays prompting them to contact companies in search of answers.
These cases typically land in the hands of overwhelmed customer service agents, who must painstakingly sift through records, investigate the issue, collect supporting evidence, determine compensation or corrective actions, and escalate if needed.
The process is not only manual and time-consuming, but also prone to human error and inefficiency frequently leaving customers feeling ignored, dissatisfied, and exasperated.
Detailed problem statement
customer-centric market, businesses across industries especially in sectors like banking, insurance, e-commerce, and utilities face a growing volume of customer disputes and complaints. These may stem from service failures, inaccurate billing, undelivered or defective products, transaction discrepancies, policy miscommunications, or delays in service resolution.
The current dispute handling process in most organizations is heavily reliant on manual workflows, involving customer service agents who must:
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Receive and interpret customer complaints across multiple channels (email, phone, chat, web portals).
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Manually validate customer identity and collect relevant details.
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Search and review multiple backend systems (CRM, billing, order management, transaction logs).
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Investigate and gather evidence or documentation (e.g., invoices, call records, delivery proofs).
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Apply internal policies to determine resolution eligibility or compensation criteria.
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Coordinate with internal departments (e.g., Finance, Legal, Operations) for approvals.
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Communicate findings back to the customer and close the case.
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This manual, fragmented approach leads to several critical issues:
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Slow Turnaround Times (TAT): Investigations can take days or weeks, especially for complex disputes.
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Inconsistency: Different agents may interpret and apply rules differently, leading to fairness concerns.
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High Operational Costs: Each case demands significant agent effort, increasing overhead.
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Error-Prone Processes: Manual data entry and judgment increase the likelihood of mistakes.
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Customer Dissatisfaction: Delays, miscommunication, and lack of transparency cause frustration and trust erosion.
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Compliance Risks: Mishandling disputes may violate consumer protection regulations, resulting in legal or financial penalties.
Detailed solution
Intelligent, automated dispute resolution solution that streamlines the end-to-end process. The ideal solution should:
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Ingest and categorize disputes automatically from multiple channels.
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Leverage AI to understand the complaint context and extract key information.
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Integrate with enterprise systems to fetch related data and validate claims.
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Apply rule-based or AI-driven logic to determine the appropriate resolution.
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Enable case tracking, exception handling, and seamless escalations.
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Provide real-time updates and transparency to customers.
By digitizing and automating the dispute management lifecycle, businesses can significantly improve resolution speed, reduce costs, ensure fairness, and enhance the overall customer experience.
Demo Video
Expected impact of this automation
Automating the end-to-end workflows for review, validation, and decision-making, AI-powered agents analyze dispute-related data and supporting documents, integrate with existing systems, and deliver faster, more accurate outcomes. This reduces manual effort, minimizes errors, and significantly shortens resolution times enabling businesses to manage high volumes efficiently while enhancing customer satisfaction with timely and consistent dispute handling.
UiPath products used (select up to 4 items)
UiPath Action Center
UiPath Agent Builder
UiPath Apps
UiPath Orchestrator
Integration with external technologies
Open AI, Email
Agentic solution architecture (file size up to 4 MB)
Sample inputs and outputs for solution execution
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Validate Customer Details:
Input: CustomerID/OrderID/PhoneNumber
Output: validate the customer against the Order and displays the OrderID of the items they purchased. -
Raise Dispute and Agent Resolution:
Input: Customer raises the query
Output: Agent classifies the query and performs sentiment analysis to provide resolution.
3.Human-in-Loop:
Input: If the Agent Sentiment score exceeds the thershold.
Output: Task will be created in Action center for the Customer center executive to provide resolution.
- Check Status
Input : Customer enters CustomerID/OrderID/PhoneNumber.
Output : Status/Resolution for the dispute raised.