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Development of AI-Powered Data Redaction Microservice for Call Recording

thinktoshare.com

Business services

Information technology

Challenge

The client, a prominent call services company, faces a challenge in providing call recording data to their B2B clients for training purposes while ensuring the confidentiality of sensitive client information (names, addresses, financial details, etc.) contained within the recordings. Sharing raw recordings is not an option due to privacy regulations and client trust.

About the Client

A leading B2B provider of call center and customer outreach services, offering services to BPOs, call centers, IT consultancies, and marketing firms.

Objectives

Develop an automated microservice to redact sensitive information from call recordings.
Ensure customizable redaction parameters based on client-defined rules.
Seamlessly integrate the microservice with the client's existing call recording systems.
Achieve a high rate of accuracy (95%-100%) in redaction.
Maintain a high rate of audio processing speed (under 30 seconds per recording).

Functional Requirements

Automated call recording processing
Customizable redaction rules (define what to redact)
Support for multiple redaction parameters (client name, address, financial info, etc.)
Secure handling of audio data
Generation of redacted audio files
Integration with existing call recording infrastructure
User-friendly interface for configuring redaction rules

Preferred Technologies

LLMs (Large Language Models)

Microservices architecture

AI/ML for audio processing

Cloud-based deployment (e.g., AWS, Azure, GCP)

Database for storing redaction rules and metadata

Integrations Required

Existing call recording system APIs
Client's authentication/authorization systems

Non-Functional Requirements

High accuracy (95%-100%)
Scalability to handle a large volume of call recordings
Low latency (under 30 seconds per recording)
High availability
Secure data storage and transmission
Maintainability and ease of updates

Estimated Business Impact

Successful implementation of this microservice will enable the client to securely provide training recordings to their B2B clients, leading to improved client satisfaction, increased business opportunities, and enhanced brand trust. It will also contribute to a safer customer outreach industry by preventing the sharing of sensitive personal data.