Lingvanex
Enterprise-grade Neural Machine Translation with local data residency and 100+ language support.
Enterprise-grade AI transcription with 99% accuracy and multi-speaker diarization.
OnlineTranscriber is a leading AI-driven Automatic Speech Recognition (ASR) platform engineered for high-fidelity transcription and multi-language translation. Leveraging advanced neural architectures, including optimized implementations of OpenAI's Whisper V3 and proprietary transformer-based models, the platform delivers near-human accuracy across 100+ languages. As of 2026, the tool has shifted towards an 'Agentic Transcription' model, where the AI doesn't just convert audio to text but also autonomously identifies action items, generates sentiment analysis reports, and suggests SEO-optimized summaries for multimedia content. Its technical stack is built on a distributed GPU-accelerated infrastructure, ensuring that a 60-minute audio file is processed in under 5 minutes. The platform emphasizes data sovereignty, offering localized data residency options and end-to-end encryption for enterprise clients. Positioned as a mission-critical tool for legal, medical, and media professionals, OnlineTranscriber integrates deeply with cloud storage providers and video conferencing tools to provide a seamless, zero-touch workflow for capturing and indexing institutional knowledge.
Uses acoustic fingerprinting to distinguish between up to 10 unique voices in a single recording with high precision.
Enterprise-grade Neural Machine Translation with local data residency and 100+ language support.
A high-performance Python library for speech data representation, manipulation, and efficient deep learning pipelines.
Enterprise-Grade Conversational Voice AI for Seamless Human-Like Interactions.
AI-driven transcription and subtitling engine for high-speed content localization.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Allows users to upload a glossary of technical terms, acronyms, and names to bias the ASR engine.
Real-time translation of transcripts into 50+ languages using a secondary LLM layer.
Neural-network based audio cleaning that isolates speech from background hums, traffic, or wind.
Precise word-level timestamps (millisecond accuracy) embedded within the JSON output.
Analyzes pitch, cadence, and word choice to determine the emotional state of speakers.
AI-driven identification and masking of PII (Personally Identifiable Information) like SSNs and credit cards.
Court reporters need high-accuracy verbatim transcripts with precise timestamps and speaker tracking.
Registry Updated:2/7/2026
Creators need to turn 60-minute audio files into blog posts, social snippets, and SRT files for YouTube.
Doctors need to document patient visits without manual note-taking to prevent burnout.