In the world of AI and machine learning solutions, there is a profound feeling of common goals and missions among providers. Today marks a very special date in the mission for Stradigi AI, and that is being included in the rollout for TensorFlow AI Service Partners program.
This initiative pulls together top practitioners of AI and machine learning across the globe to “help foster connections between TensorFlow experts, and enterprises looking to accelerate their business goals with machine learning and AI.” The roster of partners is wide-ranging in expertise, but they all have at least one thing in common: using the power and convenience of the TensorFlow platform to innovate in their respective spaces.
Who better to illustrate the positive intentions behind this initiative than Kemal El Moujahid, Director of Product Management for TensorFlow, who states in TensorFlow’s own blog “Service partners are critical in driving large adoption of AI in the enterprise. So we are excited to partner with some of the leading AI Service companies who excel at building powerful solutions with TensorFlow.”
As far as we at Stradigi AI are concerned, the capabilities that TensorFlow brings to our tech stack are essential, providing us with a core machine learning and deep learning framework that outperforms alternatives and a toolkit easily leveraged through the Keras API. And how it all comes together is in the way we are able to leverage the advantages the platform provides throughout the development process: from gaining visibility in the research phase through TensorBoard, the dashboard that provides a glimpse into models and how they learn, to the deployed solution itself, our SaaS AI business platform, Kepler. Due to this innate application in Kepler, we are proud to say that the TensorFlow platform can be found improving data-driven intelligence for customers such as Rooter and ReclameAqui.
Both thanks and congratulations are due to the team behind this promising initiative from TensorFlow to ensure that their platform’s potential is realized to its furthest extent. We can’t wait to see how this partnership program, and the technology itself, advances machine learning into the future.