Uniphore is a leading conversational AI technology company that provides solutions for customer service automation, voice biometrics, and analytics for contact center and sales teams. Their platform enables businesses to automate customer interactions and improve the customer experience using natural language processing and machine learning.
Uniphore provides AI-enabled products to businesses in various industries, such as finance, healthcare, retail, and telecommunications, which require bespoke training data development for each new customer. Developing custom annotation guidelines and manually annotating a small subset of customer calls can take months. This is followed by an analysis phase where Uniphore’s data scientists work with the business analysts and delivery team to improve the ML models, which takes additional months of effort, going between data and model iteration.
“At Uniphore, we have been involved in deploying complex ML implementations in contact centers for a few years now. However, these implementations took longer than we wanted because of the need for human-assisted annotations and model tuning. This was a significant part of the customer onboarding time. In 2022 we started looking for solutions that radically accelerate data labeling and model development to improve Time to Value (TTV) for new customers, a company-wide initiative.”Aravind Ganapathiraju, Uniphore’s VP of Applied AI
Why Uniphore chose Snorkel AI
For Uniphore, the decision to choose Snorkel Flow was based on several factors, including its ease of use, scalability, and ability to handle large amounts of training data. Snorkel Flow is a data-centric AI development platform that allows users to rapidly create and deploy AI models using a combination of human expertise and machine learning algorithms. By leveraging Snorkel Flow, Uniphore strives to accelerate its AI development cycle, reduce costs, and improve the accuracy of its conversational AI solutions.
One of the critical benefits of Snorkel Flow is its ability to handle large amounts of training data. For conversational AI solutions, having access to high-quality training data is essential for achieving high levels of accuracy and performance. With Snorkel Flow, Uniphore can use techniques, including weak supervision and programmatic labeling, to quickly and efficiently generate high-quality training data.
Another benefit of Snorkel Flow is its ability to scale. As Uniphore continues to grow and expand its business, it needs an AI development platform to meet its needs. Snorkel Flow is built to scale, allowing Uniphore to easily add new data sources, models, technologies such as LLMs, and more.
Finally, one of the key reasons that Uniphore chose Snorkel Flow is its focus on multi-persona collaboration. Unlike traditional AI development platforms, which require extensive coding and expertise, Snorkel Flow is designed to be accessible to many users, such as data scientists, business analysts, and subject matter experts. This makes it easier for Uniphore to collaborate and share knowledge across teams, resulting in faster development cycles and better outcomes. Additionally, Snorkel Flow’s guided error analysis tools can diagnose specific areas of the data that can be focused on to improve model performance, enhancing collaboration between the roles involved in the process.
“After evaluating several AI development platforms, we chose Snorkel Flow for training data and ML model development. With Snorkel Flow’s data-centric approach and powerful programmatic labeling, we can accelerate our development cycles and improve the accuracy of our models for each customer. We have started using Snorkel Flow for our internal pre-trained model development as well. Snorkel Flow’s scalability and ease of use make it an ideal platform for our needs. We’re excited to continue working with Snorkel AI to push the boundaries of conversational AI technology.”Aravind Ganapathiraju, Uniphore’s VP of Applied AI
As more businesses look to leverage NLP to improve their customer experience, platforms like Snorkel Flow and Uniphore will play an increasingly important role in driving innovation and progress in this field.