Customer profile
Name: Rapt.ai
Industry: Technology
HQ: Silicon Valley, CA
Challenge:
Rapt.ai developed a new workflow automation platform for Machine Learning. Their solution makes ML infrastructure easy to use, fast and efficient across ANY AI, ANY AI chip, and ANY platform.
To support this new platform, Rapt.ai needed a team of engineers proficient in AI and ML applications. They had the requisite bandwidth within their existing team, but not the necessary expertise required to support the new process. Hiring a new team of ML engineers would be expensive and lead to underutilization of existing talent.
iZen Solution
iZen proposed a plan to “build” the required competence within the Rapt team at a fast pace, instead of “buying” such talent from the market. A comprehensive 12-weeks skill-development program was deployed for their engineers, who were split between their US and India offices. The course was designed to help computer engineers develop AI and ML programming skills, and attain enough hands-on practice to hit the ground running.
The program was developed and delivered by a world-class expert in the field of AI and ML. The course started with the basics of AI-ML, statistics, Python programming, and data science. It then helped students understand algorithms of regression, classification, clustering, etc. — this was important as engineers supporting the new process needed to have a solid grasp on the development and fine-tuning of ML algorithms for any given domain. The program included extensive programming examples, assignments, and real-world application development.
iZen Tools Used
LEAP — Learning Engagement & Access Platform
AI/ML Engineer training program
Courseware Developed & Delivered By:
Dr. Raju Pandey
Results
In 12 weeks, Rapt’s existing team of engineers across different geographical locations were ready to support the ML platform.
Over the following months, Rapt was able to successfully roll out and support the process.
Rapt was able to improve workforce utilization, while supporting the length and breadth of the new process without significant investment in new hiring.
