CES is a Welsh company processing high volumes of customer service calls in both English and Welsh. As call volumes grew, the cost of transcription using AWS Transcribe became unsustainable. Firemind helped CES redesign its speech-to-text architecture using managed AI services on AWS, delivering the same accuracy and functionality at a fraction of the cost.
Situation
CES relied on AWS Transcribe to convert 1,000–2,000 daily calls into text. While accurate, the service became increasingly expensive as call volumes scaled.
Monthly transcription costs ranged between $2,000 and $3,000, driven by AWS Transcribe’s per-minute pricing model.
Task
CES needed to:
Dramatically reduce transcription costs
Maintain transcription accuracy and reliability
Continue supporting both English and Welsh languages
Preserve advanced capabilities such as speaker separation and PII reduction
Avoid disrupting existing batch-processing workflows
Firemind was engaged to design and deliver a cost-efficient, production-ready managed AI solution on AWS.
Action
Firemind replaced AWS Transcribe with a custom, scalable speech-to-text architecture built on AWS managed services:
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Deployed an open-source Whisper model (Turbo) on Amazon SageMaker after evaluating alternatives and selecting Whisper for superior Welsh language support
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Implemented SageMaker async endpoints with auto-scaling, allowing the platform to scale from zero to active instances based on demand
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Optimised infrastructure using ML.G4.XLarge GPU instances with NVIDIA L4 GPUs at approximately $2 per hour
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Rebuilt Transcribe-native capabilities using LLMs, including:
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Speaker separation
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PII detection and reduction
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Integrated serverless components, using AWS Lambda for payload processing and S3/SQS for orchestration
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Maintained existing workflows, preserving the customer’s four daily batch runs and S3-based ingestion
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Delivered full CI/CD automation using AWS CodeBuild for repeatable, production-grade deployments
The Results
The new managed AI platform delivered substantial and measurable business impact:
- Monthly costs reduced from $2,000–$3,000 to $300–$600
- Overall cost savings of 80–85%, equivalent to $1,400–$2,400 per month
- Maintained transcription accuracy and feature parity with AWS Transcribe
- Continued full support for English and Welsh languages
- Scalable, future-ready architecture with potential for an additional 40% cost reduction through further instance optimisation
CES achieved significant cost optimisation without compromising performance, compliance, or language coverage demonstrating how managed AI on AWS can outperform fully managed services at scale.
Conclusion & Key Takeaways
Firemind’s collaboration with MoneySuperMarket demonstrates the power of AI agents and GenAI orchestration in enhancing customer engagement and transparency.
Trust drives conversion
Speed and scalability matter
Modular AI workflows
This project has laid the foundation for MSM’s future in intelligent, explainable price comparison, blending advanced AI with a customer-first philosophy.
