Sayint

Solution Requirement

The Sayint solution includes a call recording system, a speech-to-text converter, and an analytics engine that utilizes natural language processing and artificial intelligence to understand both what customers and agents are saying and also the sentiment of their conversation. The AI algorithms are programmed in Python, and Sayint has been using the open-source PostgreSQL database management system. The database and the AI components resided on different machines, requiring data transfers that opened the system

Solution Deployment

To improve the security and performance of its solution, Sayint deployed Microsoft SQL Server 2017, which can run Python-based AI packages directly within the database, eliminating the need to transfer data between machines.

Sayint, a member of the Microsoft Partner Network, is out to change that by using powerful artificial intelligence (AI) and machine learning (ML) to monitor and analyze 100 percent of calls so that companies can better understand customer needs, improve call agent performance, and boost customer satisfaction.

Sayint typically deploys its solution in a software as a service (SaaS) model and many of its clients are familiar with Microsoft products, which has become a selling point for the SQL Server–based version of the recording system. “Our clients are comfortable with Microsoft software, and they trust that it is enterprise-ready,” explains Wagle.

Solution Benefits

Now that Sayint has incorporated SQL Server 2017 into its AI platform, the company is looking beyond just the Python incorporation and into more ways that SQL Server and other Microsoft technologies can enhance its product. A lot of customers who work with Microsoft machine learning, and one thing I hear over and over is how happy they are with the commitment and resources Microsoft has put into it.