Guides, product updates, and technical notes on AI agents, speech-to-text, token optimization, and privacy-first voice workflows.
20 articles
I've shipped async transcription pipelines handling 800+ hours of audio daily. Here's the webhook architecture, retry logic, and idempotency that work at scale.
Wire Privocio speech-to-text into a LangChain agent: STT with the OpenAI Python client, Agent output mode for token savings, and an end-to-end voice-to-LLM example.
A decision framework for teams evaluating an OpenAI Whisper API alternative — pricing at 10/50/200 hours, privacy, output modes, self-hosting, and a one-line migration path.
Transcribe audio in Go using the OpenAI Go client with a Privocio base URL. Whisper-compatible batch transcription for backend services and AI agents.
Transcribe audio with cURL and Privocio's speech-to-text API. Batch uploads, OpenAI-compatible routes, and SSE streaming from your terminal or CI pipeline.
Learn how to use a JavaScript speech-to-text API with fetch, FormData, the OpenAI Node SDK, SSE streaming, and Privocio's private STT infrastructure.
I've tested both real-time and batch transcription in production. Here's the exact latency and cost trade-off — and how to choose the right mode for your AI agent workload.
Learn how to use a Python speech-to-text API to transcribe audio files with httpx, Bearer authentication, Whisper-compatible models, and Privocio's private STT infrastructure.
I've added voice to 20+ chatbots. Here's the three integration patterns that actually work in production, with code examples and cost comparisons.
I've built voice pipelines for six production AI agents. Here's the architecture that actually works — STT, LLM, TTS, privacy, latency, and token optimization.
I've deployed private transcription for seven law firms. Here's what attorney-client privilege actually requires from your transcription vendor.
I've built voice-enabled AI agent pipelines for production workloads — here's the complete guide to choosing and integrating speech-to-text.
I've tested every privacy approach for transcription — end-to-end encryption is the only one that genuinely protects your data end-to-end.
I've set up self-hosted Whisper for six production deployments. Here's the honest breakdown of Docker, native, and managed open-source options.
After deploying private speech-to-text for 20+ production teams, here's the complete guide to choosing the right secure transcription API.
Data residency for speech-to-text: where does your audio actually go? I've traced transcription pipelines across AWS, Google Cloud, and Azure to find out.
I tested transcript formats across 500+ hours of AI agent audio. Agent-mode transcripts cut LLM tokens by 40% — here's the exact math and the one-parameter fix.
After deploying GDPR-compliant transcription for EU legal and financial clients, I've documented exactly what you need to do.
I've deployed both on-premise and cloud speech-to-text at scale. Here's the real breakdown on privacy, cost, and latency — with actual numbers from production workloads.
I've helped three healthcare organizations set up HIPAA-compliant transcription. Here's what vendor marketing doesn't tell you about BAA requirements, data handling, and audit trails.
Turn speech into structured, agent-ready context while keeping costs predictable.
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