Gladia, an AI transcription and audio intelligence provider, has completed a €14.7 million Series A funding round. The company will use the funding to develop an end-to-end audio infrastructure – starting with a new real-time audio transcription and analytics engine – enabling voice-first platforms to deliver more value to their users across borders with cutting-edge AI.
The Series A funding round was led by XAnge, with participation by Illuminate Financial, XTX Ventures, Athletico Ventures, Gaingels, Mana Ventures, Motier Ventures, Roosh Ventures, and Soma Capital. Founded in 2022, Gladia has now raised a total of USD $20.3 million, with earlier seed investments headed by New Wave, Sequoia Capital (as part of the First Sequoia Arc program), Cocoa, and GFC.
“Gladia represents the qualities we like to champion at XAnge: a bold, global tech team at the forefront of AI innovation, with a proven business model to unlock new opportunities across industries,” said Alexis du Peloux, Partner, XAnge. “In a fast-paced AI environment, Jean-Louis Quéguiner and his team have executed extremely well, and we are proud to back Gladia for the Series A.”
“I founded Gladia for a very personal reason – I was frustrated that existing audio transcription services were not able to understand my French accent,” explained Jean-Louis Quéguiner, CEO and Co-Founder, Gladia. “Our international team and customers often switch between languages during meetings, but finding a transcription solution that can handle different languages and accents simultaneously was impossible.”
Given that most speech recognition models today are trained predominantly on English audio data and are therefore inherently biased, Gladia prioritized building the first real-time product that is truly multilingual. The new fine-tuned engine delivers advanced real-time transcription in over 100 languages, along with enhanced support for accents and the unique ability to adapt to different languages on the fly.
Gladia’s new engine is unique in its ability to extract insights from a call—like the caller’s sentiment, key information, and conversation summary—in real-time. This means it takes less than a second to generate both transcript and insights from a call or meeting using Gladia.
Building an accurate, low-latency, and multilingual engine in-house is a complex and resource-intensive task. It requires extensive expertise in language understanding, real-time data handling, with continuous optimization and maintenance. Real-time models require more computing power and may struggle to produce accurate output immediately due to limited context.
Gladia’s new product allows companies to bypass these challenges. The real-time speech-to-text engine boasts an industry-leading latency of under 300 milliseconds without compromising accuracy, regardless of the language, geography, or tech stack used.
“Companies are spending valuable time and resources trying to incorporate multiple AI functions into their existing platforms,” added Jonathan Soto, Co-Founder and Chief Technology Officer, Gladia. “Our single API is compatible with all existing tech stacks and protocols, including SIP, VoIP, FreeSwitch, and Asterisk. This allows us to easily integrate real-time transcription and analysis into our customers’ AI platforms, so they can focus on delivering the best services to their end users.”
Gladia will use the new capital to advance its R&D efforts and soon bring to market a one-stop AI toolkit for audio and expand its product offering with additional à la carte models—including large language models (LLMs) and retrieval-augmented generation (RAG). With several design partners in the contact-center-as-a-service (CCaaS) segment, the company is currently piloting an agent-assist solution powered by Gladia’s real-time AI engine. Additionally, Gladia will continue to expand its talent base as it prepares for international expansion.
Read the orginal article: https://www.eu-startups.com/2024/10/paris-based-gladia-raises-e14-7-million-to-launch-multilingual-real-time-audio-transcription-and-analytics-engine/
