Cutting transcription cost per audio hour for meeting assistants

Transcription costs are presented as a central factor in meeting-assistant profitability, with effective expenses shaped not only by base speech-to-text rates but also by add-on features, billing increments, audio storage, data transfer, duplicate requests, and operational overhead. The discussion argues that managed APIs can be more economical than self-hosted open-source models at lower volumes because idle GPU capacity, engineering maintenance, scaling, and reliability issues raise total cost of ownership. It compares pricing approaches among providers and promotes Gladia’s bundled plans, claiming rates from $0.61 per hour on a starter tier to $0.20 per hour with committed volume, including diarization, translation, sentiment analysis, entity recognition, and summarization. Accuracy is framed as equally important because transcription errors can impair summaries, CRM updates, and other downstream AI outputs, particularly for speaker attribution, names, accents, and multilingual audio. Recommended cost controls include using compressed audio formats, favoring asynchronous transcription over real-time processing when post-meeting output is sufficient, implementing idempotent requests and deduplication, setting usage limits, retaining raw audio only briefly, and negotiating enterprise agreements at larger scale for pricing, compliance, data-retention, and service-level requirements.

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