Speech-To-Text
Large Language Models (LLMs) are at the forefront of the democratization of AI and they continue to get more advanced. However, LLMs can suffer from performance issues, and produce inaccurate, misleading, or biased information, leading to poor user experience and creating difficulties for product builders.
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.
Speech-To-Text
From virtual meeting assistants to call center platforms, the need for multilingual transcription to serve a global user base is on the rise. As a product builder looking to implement automatic speech recognition (ASR) into your app, you're likely searching for a solution that can transcribe speech into multiple languages in real time and translate it accurately into the language of choice.
Product News
Real-time audio AI is transforming the way we work and build software. With instant insights from every call and meeting at their fingertips, customer support agents and sales reps will be able to reach new levels of efficiency and deliver a more delightful customer experience across borders.
