ASAPP Chief Scientist Ryan McDonald filters out the signal from the noise regarding leveraging Generative AI like ChatGPT and other LLMs (large language models) for CX Read more

End-to-end architecture improves the scalability and performance of machine learning models for speech transcription to serve enterprise contact center needs better. Read more

CX teams can identify and react to unexpected customer behavior faster using ASAPP anomaly detection. Learn what makes our models so effective. Read more

Dialogue State Tracking has run its course. That’s why we’re establishing a new Action-Based Conversations Dataset. Read more

Neural Network Compression. What is it, and why does it matter? Here’s a look at what led to the development of DenseNets for parameter-efficient networks with significantly more accurate predictions. Read more

Ryan McDonald, PhD shares his excitement about joining ASAPP, and the opportunity to build revolutionary products that are AI-centric from concept. Read more

ASAPP has an innovative vision for how to solve CX performance problems. To achieve this vision, our research team continually pushes the boundaries of what’s possible in AI. Watch now

Take CX performance to new heights. Use automation to support your agents in serving your customers well—in a way that chatbots alone simply can’t. Read more

Highly expressive and efficient neural models can be designed using SRU++ with little attention computation needed. Read more

Overcome the limitations of RPA with AI-driven automation that helps your agents more efficiently navigate a myriad of back office systems. Read more