Development of an Offline Voice Feedback and Analytics Platform for Field Service Monitoring

The client faces difficulties in monitoring the quality of service provided by employees and third-party vendors in remote locations with unreliable internet connectivity. The current processes lack real-time, accessible feedback mechanisms, and do not support automatic identification of key action points within feedback texts, hindering timely performance evaluations and operational improvements.

A large industrial enterprise operating multiple facilities and field operations across remote regions, requiring efficient performance monitoring and quality feedback collection from both on-site employees and third-party vendors.

• Implement an offline-capable voice feedback system enabling field managers to record and store feedback locally in areas with poor or no internet access.
• Develop a mobile application that converts speech to text instantly, allowing quick sending of feedback via email or internal channels.
• Create a web-based analytics dashboard providing visual insights such as top and bottom performers, sentiment analysis, and feedback trends.
• Integrate natural language processing to automatically extract action items and key phrases from textual feedback for targeted improvements.
• Establish a scalable system capable of handling increasing volume of feedback data and providing real-time updates when connectivity permits.

• Mobile application for voice feedback recording with local storage capability
• Automatic speech-to-text conversion using embedded speech recognition frameworks
• Email or message-based feedback sharing directly from the app
• Action point highlighting and key phrase extraction through natural language processing
• A web dashboard for aggregating and analyzing feedback data with statistical and sentiment summaries
• User management for access control and role-based permissions

• Speech recognition APIs (e.g., Apple, Google) for voice-to-text conversion
• Natural language processing services (e.g., Amazon Comprehend, open-source NLP libraries)
• Email and messaging services for feedback sharing
• User authentication and role management systems

• Offline functionality to support voice recording in areas with no internet connectivity
• Automatic synchronization of saved feedback when internet access resumes
• High accuracy of speech recognition tailored for field environment noise conditions
• Sentiment analysis accuracy of at least 85%
• System scalability to handle thousands of feedback entries daily
• Data security and compliance with industry standards for sensitive operational information

The new system is expected to significantly streamline feedback collection from remote field locations, reducing the time between service delivery and performance evaluation. By enabling offline recording and automated analysis, the client can improve data-driven decision-making, identify underperforming vendors or employees swiftly, and enhance overall operational quality. Anticipated improvements include increased feedback volume, more actionable insights through automatic highlighting, and improved employee and vendor performance, ultimately leading to higher operational efficiency and reduced downtime.