News & Blog
Perspectives on the evolving tech landscape
Audio-to-LLM: From audio to structured intelligence in one API
TL;DR: Gladia's Audio-to-LLM runs transcription, diarization, and LLM analysis in a single POST request. Pass a 'prompts' array, get structured outputs back in one webhook. No pipeline to build
April 08, 2026
Audio-to-LLM: From audio to structured intelligence in one API
TL;DR: Gladia's Audio-to-LLM runs transcription, diarization, and LLM analysis in a single POST request. Pass a 'prompts' array, get structured outputs back in one webhook. No pipeline to build
April 08, 2026
Audio-to-LLM: From audio to structured intelligence in one API
TL;DR: Gladia's Audio-to-LLM runs transcription, diarization, and LLM analysis in a single POST request. Pass a 'prompts' array, get structured outputs back in one webhook. No pipeline to build
April 08, 2026How enterprise teams cut latency by 60% with UPMIC edge inference
A deep dive into how three Fortune 500 companies deployed UPMIC's on-device AI to slash cloud round-trip times and improve real-time decision making at the edge.
March 22, 2026Benchmarking real-time STT: UPMIC vs cloud-only pipelines
We ran 10,000 hours of multilingual audio through five leading STT engines. Here's how UPMIC's hybrid approach stacks up on accuracy, latency, and cost.
March 15, 2026Build a voice-controlled dashboard in 30 minutes with UPMIC SDK
Step-by-step tutorial: from installing the SDK to streaming transcription results into a live React dashboard with speaker diarization and intent detection.
March 10, 2026Introducing UPMIC v2.0: Faster inference, smaller footprint
Our biggest release yet brings 2x faster model loading, 40% smaller binary size, and native support for the latest Qualcomm and MediaTek chipsets.
February 28, 2026From prototype to production: a startup's journey with UPMIC
How a 5-person team used UPMIC's chip agency program to go from concept to a shipping consumer device in under 6 months, without hiring a single ML engineer.
February 20, 2026Deploying custom wake-word models on UPMIC hardware
Learn how to train, quantize, and deploy a custom wake-word detection model that runs entirely on-device with sub-200ms response time.
February 12, 2026