TL;DR:
- Tecton partners with Google Cloud, offering its feature platform to supply high-quality data for machine learning models.
- Tecton Feature Platform is now available on Google Cloud Marketplace, enabling customers to use Google Cloud credits for the service.
- The platform automates data collection, preparation, management, and updates for training machine learning models.
- Google Cloud’s AI and data services, combined with Tecton’s platform, accelerate ML model development while controlling costs.
- Tecton fills a critical gap for Google Cloud customers, bringing advanced ML feature engineering capabilities.
- Businesses can leverage the partnership to build better ML models efficiently and foster collaboration.
Main AI News:
In a groundbreaking strategic alliance, Tecton, the pioneering machine learning startup, has joined forces with Google Cloud, unleashing the formidable potential of the Tectonic feature platform to empower users with top-notch data for their machine learning models.
The union between Tecton and Google Cloud brings forth the cutting-edge Tecton Feature Platform, a powerful tool that seamlessly integrates with Google Cloud’s AI and data services. The result? An exponential acceleration in the development of machine learning models while maintaining optimal cost management, as revealed by Tecton.
Excitingly, the Tecton Feature Platform now graces the Google Cloud Marketplace, allowing customers to leverage their Google Cloud credits to access this exceptional service. (It’s worth noting that Tecton also boasts a similar collaboration with Amazon Web Services.)
Mike Del Balso, the visionary co-founder and CEO of Tecton, enthusiastically expressed, “This groundbreaking technology has been exclusive to other cloud providers, but now, for the very first time, we’re bringing this solution to Google Cloud customers.” Tecton, a trailblazing enterprise based in San Francisco, emerged in 2019, founded by the brilliant minds behind Uber’s renowned Michelangelo machine learning platform. The company has soared to new heights, accumulating an impressive $160 million through multiple funding rounds.
So, what sets Tecton apart? The platform offers an automated system for gathering, preparing, managing, and updating vast volumes of high-quality data essential for training machine learning models. This impeccable data flow ensures that real-time predictive and generative AI applications operate flawlessly. Tecton’s capabilities span a wide range of applications, from dynamic pricing, customer scoring, and recommendation engines to automated loan processing and fraud detection systems.
“These are the critical decisions that numerous businesses face, and they must execute them at scale, at speed, and with utmost reliability,” Del Balso emphasized.
Developing the pipelines to transform batch, streaming, and real-time data into machine learning “features” is typically a complex and daunting task, which often results in the failure of many machine learning initiatives. Del Balso noted, “It’s not uncommon for our customers to have literally thousands of features that power their models.”
Enter Google Cloud, armed with its Vertex AI system for training and deploying machine learning models and its ability to customize large language models for AI-powered applications. Additionally, Google Cloud offers a suite of indispensable open-source tools such as TensorFlow and Kubernetes. Vital data processing infrastructure services like DataProc and BigQuery play a significant role in the realm of ML projects.
Tecton becomes the “connective fabric,” seamlessly binding these systems together and facilitating the construction of production-ready ML features. With Tecton’s automation, the ML feature lifecycle, encompassing feature definition, data transformation, online serving, and operational monitoring, becomes effortlessly efficient.
The Tecton platform acts as a guiding light for developers, elevating their machine learning models by harnessing the power of top-tier data. By streamlining the data transformation and management phases, ML systems can be deployed into production at lightning speed. Moreover, Tecton adds a much-needed layer of enterprise management and collaboration, often missing from other ML initiatives, ensuring greater success.
Enterprises and strategic service providers in the AI and machine learning landscape can now leverage the formidable combination of Tecton and Google Cloud to enhance their efficiency and deliver superior results to their valued customers. Del Balso emphasized, “This is just another option to make their customers more successful.”
Manvinder Singh, Google Cloud’s Managing Director of Partnerships, expressed immense excitement about the partnership, stating, “We are delighted to partner with Tecton to bring advanced Machine Learning feature engineering capabilities to Google Cloud. Via this partnership, customers can further accelerate the building of machine learning applications via Tecton and Google Cloud’s AI and data services.“
Conclusion:
The strategic partnership between Tecton and Google Cloud signifies a significant advancement in the AI and machine learning market. By integrating Tecton’s powerful feature platform with Google Cloud’s robust AI and data services, businesses gain access to accelerated ML model development and enhanced data-driven decision-making capabilities. This collaboration opens up new possibilities for enterprises to build highly efficient and reliable AI applications, thus positioning them competitively in the evolving market landscape.
