User-generated content has become a cornerstone of the internet-driven economy. As part of this shift, various platforms have emerged to provide easy-to-use tools to create high-quality video content in a matter of minutes — with AI transcription playing a foundational role in their product development.
VEED is one of the leading editing platforms today, relying on Gladia’a transcription API to empower video content creators around the globe. Read on to find out which features they improved thanks to our API and the impact of speech-to-text on VEED’s roadmap, user engagement, and growth.
VEED was founded in 2018 by Sabba Keynejad and Tim Mamedov with the aim of democratizing the visual content industry. To deliver on that vision, the company offers a video recording and editing platform that enables anyone to create high-quality video content in minutes without specialized skills.
Originally designed for individual content creators, VEED is currently expanding into the B2B segment, providing its services to communication professionals and the like.
With a staggering 10M active monthly users on its platform uploading one video every second, the company is delivering new features and expanding its user base across geographies.
The ability to roll out new, value-adding features as part of its core offer, is among top strategic priorities for platforms like VEED when it comes to user acquisition and engagement.
Among the core VEED features today are automatic subtitles and editing tools like Magic Cut and Silence Removal. The editing toolkit allows users to automatically remove errors, pauses, and repetitive words from raw footage in a single click, transforming long, imperfect footage into short, punchy edits optimized for social channels.
All these features rely on Transcription as their core, so having an accurate, reliable provider capable of transcribing speech across languages was key.
The issue they encountered, however, was that a lot of existing alternatives didn’t provide satisfactory results on non-English languages based on internal benchmarks run by the VEED team to assess API providers.
In this context, VEED was looking to deploy a high-quality transcription and audio intelligence API to integrate with its platform, based on the following specifications:
Enter Gladia! With Gladia, the VEED team was able to implement:
By working with the Gladia team to iterate and scale up, VEED’s team saw a noticeable impact on their own customers, from users praising the quality of the transcription to prospects converting specifically after trying it out.
The team at VEED is continuing to explore the possibilities that transcription brings to their AI product, and is now considering how they will leverage it in the future with upcoming features requiring advanced multilingual transcription and metadata extraction.
We're thrilled to be part of this amazing journey with them, and thank VEED for putting their trust in us! We look forward to partnering with more customers to tackle new challenges, and make speech AI more accessible to media companies worldwide.
Having read this case study, do you feel like Gladia could be the right fit for your business too?
Don't hesitate to contact our sales team to discuss this in more detail. Beyond video and podcast platforms, we cater to a range of use cases, including virtual meetings, call centers, workspace collaboration, and more.
At Gladia, we built an optimized version of Whisper in the form of an API, adapted to real-life professional use cases and distinguished by exceptional accuracy, speed, extended multilingual capabilities, and state-of-the-art features, including speaker diarization, code-switching and word-level timestamps. Our latest model, Whisper-Zero, that removes hallucinations and improves accuracy across languages is available now.
Speech-To-Text
Over the last few years, Large Language Models (LLMs) have become accessible and transformative tools, powering everything from customer support and content generation to complex, industry-specific applications in healthcare, education, and finance.
Case Studies
In recent years, fuelled by advancements in LLMs, the numbers of AI note-takers has skyrocketed. These apps are increasingly tailored to meet the unique needs of specific user groups, such as doctors, sales teams and project managers.
Speech-To-Text
It happens all the time. A user submits a query to a large language model (LLM) and swiftly gets a response that is clear, comprehensive, and obviously incorrect.
