I need an API to transcribe thousands of customer support calls. What should I use?

For thousands of customer support calls, you want a transcription API that is:

• Accurate on real-world call audio: accents, crosstalk, noisy lines
• Scalable and batch-friendly
• Fast enough for your volume
• Good with long recordings
• Ideally supports speaker diarization, timestamps, and domain adaptation if you need analytics later

Best options to consider

1) OpenAI Speech-to-Text API

Good if you want strong transcription quality and a simple developer experience.

Why use it:

• Strong accuracy on messy audio
• Easy API integration
• Good for large-scale automation
• Useful if you may later want summaries, QA, or categorization on top of transcripts

Best for:

• General customer support transcription
• Pipelines where you’ll process transcripts afterward with LLMs

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2) Deepgram

Very popular for call center transcription.

Why use it:

• Built for high-volume audio
• Often excellent on call audio
• Supports speaker diarization, timestamps, punctuation, word-level confidence
• Good real-time and batch options

Best for:

• Call-center style workloads
• Teams wanting transcription plus speech analytics features

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3) AssemblyAI

Also strong for support call transcription and downstream analysis.

Why use it:

• Good transcription quality
• Strong built-in features like sentiment, chaptering, summarization, and entity detection
• Easy async workflow for long files

Best for:

• If you want transcription plus analytics in one vendor

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4) Google Speech-to-Text / AWS Transcribe / Azure Speech

Good enterprise choices if you’re already in those cloud ecosystems.

Why use them:

• Enterprise procurement/compliance advantages
• Familiar infrastructure
• Scalable

Best for:

• Teams already committed to GCP/AWS/Azure
• Workloads where vendor consolidation matters

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My practical recommendation

If your goal is specifically transcribing thousands of customer support calls, I’d shortlist:

1. Deepgram — best fit for call-center style transcription features
2. OpenAI Speech-to-Text — strong accuracy and easy integration
3. AssemblyAI — good if you want extra transcript analysis features

What to look for before choosing

Ask each vendor about:

• Batch transcription pricing per audio minute
• Maximum file length
• Speaker diarization quality
• Support for telephony audio (8 kHz, mono, VoIP)
• Turnaround time / throughput
• Data retention and privacy controls
• Language support
• Word-level timestamps
• Confidence scores
• Webhooks / async job support

A simple decision rule

• Want best call-center tooling → Deepgram
• Want simple API + strong general transcription → OpenAI
• Want transcription + built-in analytics → AssemblyAI
• Already on a cloud provider and want procurement simplicity → Google/AWS/Azure

If you want, I can help you narrow this down by your constraints:

• monthly call volume
• average call length
• need for speaker diarization
• languages/accents
• budget
• whether you need real-time or batch processing