Introduction

In today's fast-paced world, customers demand quick and efficient service delivery. Providing timely and accurate service is crucial for technicians working in the field, especially in industries like energy and appliance repair. Traditional methods often involve manual processes, leading to delays, errors and inefficiencies.

Field-service teams often rely on manual, paper and phone-based processes. Service tickets are tracked in spreadsheets that obscure essential details. Scheduling and inventory checks are handled through emails or outdated systems, often resulting in missed appointments or incorrect parts. Technicians submit free-form notes, leading to inconsistent documentation and delayed feedback. These inefficiencies increase response times, cause errors and limit real-time visibility.

Introducing SwiftFixAI, an innovative solution powered by GenAI on AWS that streamlines technician workflows, improves customer satisfaction and reduces operational overhead. By leveraging cutting-edge services powered by Amazon Web Services (AWS), SwiftFixAI transforms how technicians handle service calls, making their jobs easier while enhancing customer experience.

The need

Due to siloed data and manual workflows, field service teams often face operational bottlenecks.

Technicians struggle with:

• Lack of access to real-time part availability, warranty details and previous service history
• Delays caused by manual inventory checks and unclear issue descriptions
• Inefficient coordination with support teams due to scattered documentation

Customers encounter:

• Inconsistent service experiences and long wait times
• Limited visibility into part availability or warranty eligibility
• Difficulty choosing between repair and replacement without contextual guidance

These gaps result in extended service cycles, increased costs and reduced satisfaction on both sides.

The solution

SwiftFixAI addresses these challenges by integrating Generative AI (GenAI) into every service process step. By utilizing AI-driven features like call recording transcription, action item extraction and real-time inventory queries, repair v/s replacement analysis, the solution enhances field operations for technicians and delivers a smooth, stress-free customer experience.

Solution workflow

Technical architecture

SwiftFixAI is powered by a combination of AWS services, which work in tandem to provide seamless service delivery. Below is the architecture breakdown:

1. Customer interaction via app

   The customer initiates contact through the application via chatbot or by calling the support helpdesk using Amazon Connect. Three interaction channels are supported:

   1. Photo upload: Capture and submit an image of the faulty appliance
   2. Text input: Type a description of the problem in the chat window
   3. Voice call (Amazon Connect): Speak to a support agent—calls are recorded and securely stored for further processing
2. Ingestion, storage and preprocessing 
   1. Amazon API gateway: Exposes secure endpoints to receive chats, images and voice data
   2. AWS Lambda: Orchestrates the routing and processing of incoming data
   3. Amazon S3:
      1. Raw bucket: Stores original inputs (audio, images, chat logs)
      2. Processed bucket: Holds extracted and transcribed content in structured JSON format
   4. Preprocessing logic:
      1. Voice → Amazon Transcribe: Converts recorded speech into text
      2. Image → Amazon Textract: Extracts key fields such as model number, warranty and issue description
3. LLM analysis and ticket generation
   1. Amazon Bedrock Agent (Claude Haiku 3.5/ Amazon Nova Pro) processes the extracted and transcribed data to generate:
      1. A clear Issue Summary
      2. Warranty and Product Info
      3. Next Steps or Diagnostics
      4. Repair vs. Replacement Recommendation
   2. Automated ticket creation:
      1. AWS Lambda triggers ticket creation, populating it with metadata, problem summary and customer context
      2. Ticket is pushed to any of the integrated CRM tools/ ticketing platforms:
         1. Zendesk
         2. ServiceNow
         3. Salesforce
      3. The same ticket is also stored in Amazon DynamoDB for technician workflows and system-of-record purposes
4. Knowledge base integration for recommendations
   1. Data sources:
      1. Product specifications, warranty policies
      2. Inventory levels and restock timelines
      3. Labor costs and part prices for repair-vs.-replacement logic
   2. LLM decision support:
      1. Fetches contextual knowledge
      2. Provides personalized, cost-effective guidance for both the technician and customer
5. Technician response
   1. Amazon API gateway and AWS Lambda: Support technician portal functions, including ticket retrieval and update actions
   2. Amazon DynamoDB:
      1. Central store for tickets, inventory and service data
      2. Technicians use it to:
         1. View LLM-generated summaries
         2. Enquire and reserve the required parts
         3. Plan the site visit with all relevant context
6. Execution and closure
   1. On-site repair:
      1. The technician performs the repair/replace and updates the ticket status and notes via the app
   2. Digital sign-off and feedback:
      1. Customer signs off digitally and submits a satisfaction rating
      2. All updates are saved in DynamoDB and synced with the ticketing platform
   3. Automated resolution summary:
      1. A final summary is generated using Amazon Bedrock based on the technician notes and added to the customer record

Benefits: How SwiftFixAI helps technicians and customers

For technicians:

• Quick access to information: Technicians can instantly see customer details, past service history and which parts are available—no need to call or check manually
• Easier problem solving: The system uses AI to summarize conversations and highlight key action items, helping technicians figure out the issue faster
• More jobs in less time: Because everything is automated—ticket creation, part lookup and scheduling—technicians can fix more appliances in a day

For customers:

• Faster fixes: Customers get their appliances repaired quickly because the system cuts down on delays and confusion
• Clear updates and smarter choices: Customers get regular updates and can see whether it's better to repair or replace a product, helping them make the right decision
• Enhanced experience: With fast service and accurate problem detection, customers are happier and more satisfied

Conclusion

SwiftFixAI delivers an AI-driven field service platform that unifies intelligence, automation and contextual insights. Leveraging AWS services such as Amazon Bedrock, Amazon Nova Pro LLM, Amazon Transcribe, Amazon Textract, AWS Lambda and Amazon DynamoDB, etc., it equips technicians with precise tools and data at every step. SwiftFixAI sets a new standard for operational efficiency and customer satisfaction in the Energy and Utilities industry by streamlining diagnostics, automating ticket creation and optimizing parts planning.

No more slow ticket handling or manual data searches. Instead, enjoy instant insights, seamless communication and faster on-site repairs. SwiftFixAI transforms appliance maintenance into a truly efficient and reliable experience, setting a new standard for field service excellence.