Integrating a speech-to-text API into your own systems
Calling a transcription API is rarely the hard part, a single POST request does it. Running it in production is: what happens on a timeout halfway through a two-hour recording, how to verify a webhook signature, and when polling is the better choice after all. These articles cover REST, webhooks, live streaming and MCP for AI agents, each with code you can run.
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Articles in this topic
Building AI Agents with MCP and Transcription Data
How to expose your transcript archive to Claude Desktop and custom agents over the Model Context Protocol: securely, queryably, with EU data residency.
Transcription API vs Self-Hosted Whisper: When to Choose Which
Honest cost and engineering comparison: running Whisper on your own GPU vs using a transcription API at €0.18/hour. Total cost of ownership, latency, accuracy, when self-hosting actually pays off.
Giving AI Agents Access to Your Audio: Transcription via MCP
How to make a year of meeting recordings, interviews, and calls queryable by AI agents like Claude and ChatGPT – using transcription, MCP, and the right retention policy.
Speech-to-Text API for Developers: Getting Started with DeepScript
Integrate speech-to-text into your app with the DeepScript API. Code examples for cURL, Python, and JavaScript. 99 languages, GDPR-compliant, hosted in Germany.
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Other topics
Privacy & compliance
What GDPR, professional confidentiality and MiFID II actually require when you transcribe.
Usage & workflow
From raw recording to usable document: interviews, subtitles, minutes, academic transcripts.
Market & selection
Comparing providers on the facts: pricing, data residency, languages, API depth, and when each fits.
Transcription that protects your data
Three transcriptions free, no credit card. Data stays in Germany.