(SeaPRwire) – BOSTON, MA – 23/03/2026 – (SeaPRwire) – Modulate has unveiled a novel speech-to-text API intended to redefine how organizations process and interpret conversational audio at scale. The newly launched Velma Transcribe is framed as a cost-effective, high-performance transcription solution tailored to fulfill the rising demand for real-time voice data analysis across industries, from customer service to social platforms and AI-driven tools.
The announcement emphasizes a broader industry movement toward enhancing the accessibility and economic viability of voice intelligence infrastructure. By markedly lowering the cost threshold for transcription, Modulate’s latest offering empowers organizations to extend the use of voice data across a wider array of applications, including real-time voice agents, analytics pipelines, and global communication platforms.
Velma Transcribe is built upon Modulate’s Ensemble Listening Model (ELM), a research-backed method that coordinates multiple specialized transcription models to optimize performance. This ensemble-based framework boosts transcription accuracy, cuts down latency, and improves cost efficiency compared to traditional single-model systems. The platform has shown strong results on well-known benchmarks such as Earnings-22 and the AMI Meeting Corpus, especially when handling complex, multi-speaker conversational settings.
Company leaders stress that the solution goes beyond basic transcription capabilities. While many systems focus solely on converting speech to text, Velma Transcribe incorporates deeper contextual understanding, enabling a broader range of conversational insights. Simultaneously, the API is designed to stay user-friendly for developers who need fast, reliable transcripts without extra analytical complexity.
Beyond its transcription functions, the platform includes a set of enterprise-focused features, such as emotion detection across over 20 categories, accent recognition spanning more than 20 variations, and multilingual support covering over 70 languages. It also offers advanced capabilities like speaker diarization, personally identifiable information (PII) detection and redaction, and real-time streaming support for live applications.
One of Velma Transcribe’s most prominent features is its pricing model. With transcription costs reduced to roughly $0.03 per hour of audio, the platform delivers a significant reduction compared to current market rates. This pricing structure enables enterprises to process large volumes of voice data more affordably, creating new opportunities for data-driven decision-making and monetization strategies.
The system is engineered to perform reliably in real-world conversational settings, where overlapping speech, interruptions, diverse accents, and background noise often challenge standard transcription tools. Benchmark results show that Velma Transcribe significantly lowers error rates compared to several established solutions, reinforcing its suitability for enterprise-scale deployment.
To support production-level applications, the platform includes features like batch and streaming transcription endpoints, structured outputs with timestamping, sub-second latency for live use cases, and a zero data retention policy aimed at enhancing privacy and compliance. Supported by ISO 27001-certified security practices, these features position the solution for secure deployment in regulated and data-sensitive environments.
Velma Transcribe is part of Modulate’s broader Velma 2.0 suite of voice intelligence models, which aim to equip AI systems with a more advanced “listening layer.” This approach allows organizations to move beyond simple transcription to deeper conversational understanding, supporting use cases such as fraud detection, sentiment analysis, compliance monitoring, and real-time operational insights.
The solution is available immediately, with usage-based pricing designed to accommodate both small-scale deployments and high-volume enterprise workloads.
About Modulate
Modulate is a voice intelligence technology firm focused on developing AI models and APIs that enable scalable understanding of real-world conversational audio. Its solutions combine speech recognition, acoustic analysis, and contextual processing to deliver accurate, explainable, and cost-effective voice intelligence for enterprises and developers.
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