AI applications are experiencing a significant boom, but ensuring the success of these applications requires high-quality data. Reliable, complete, and accurate data is crucial for AI systems to function effectively. Seattle-based startup Gable.ai aims to address this challenge with its data collaboration platform. With $7 million in seed funding, Gable.ai is poised to revolutionize the way software and data/ML developers build and manage high-quality data assets. Investors have already dubbed it the “GitHub for data,” a title that resonates with other data companies like Kaggle and Hex who are also investing in Gable.ai.
Gable.ai’s platform enables data producers and consumers to collaborate seamlessly. It tackles the problem of breaking changes in critical data workflows within existing infrastructure. The platform offers data asset recognition by connecting various data sources, data contract creation to establish ownership and constraints, and data contract enforcement through continuous integration and continuous deployment within the GitHub framework. Chad Sanderson, CEO, and co-founder of Gable.ai, expresses the need for a communication tool similar to GitHub within the data domain, as software engineers already benefit greatly from GitHub in their work. Gable.ai aims to fill this void.
Gable.ai was founded by Chad Sanderson, Adrian Kreuziger, and Daniel Dicker. Prior to their venture, they led the data department at Convoy, a $4 billion digital trucking network. Convoy facilitated the movement of thousands of truckloads daily across the country using an optimized network of carriers. However, despite having modern data technologies, trust in the data was severely lacking. Issues related to data quality, outages, and unusable rows of data plagued the company. Sanderson vividly describes the complexity that even simple questions like “How many shipments did we do over the past 30 days?” posed for data scientists and analysts.
The consequence of poor data quality was evident in both analytics and machine learning operations at Convoy. Complex systems generated highly sensitive models, and it was up to data scientists to understand which specific data inputs were needed. When the quality of data faltered or experienced sudden changes, these sensitive models would break down, leading to inaccurate predictions. Sanderson believes that bridging the communication gap between software engineers and ML developers was the key to resolving these issues. Once this gap was closed, data quality significantly improved, benefiting the company as a whole.
Addressing communication problems surrounding data changes is vital for scaling AI effectively. Without a proper change management system, AI scalability is nearly impossible. Large tech companies like Google, Meta, and Amazon have resorted to employing multiple data engineers to handle the management of data when new machine learning models are introduced. However, smaller companies like Convoy face challenges due to limited resources. Sanderson explains that Convoy’s data engineering team consisted of only six people, making it impossible to assign multiple engineers to every new ML model. Gable.ai’s solution fills this void by providing data contracts, a breakthrough in data management that establishes a new emerging data primitive.
Gable.ai’s groundbreaking data contracts represent a significant contribution to the data landscape. These contracts act as a basic data type, facilitating better organization and management of data. Sanderson’s creation of the “Data Quality Camp,” a Slack community of over 8,000 dedicated data practitioners, has helped drive engagement and awareness around these concepts. The involvement and endorsement of Gable.ai by founders of successful data companies such as dbt Labs, Monte Carlo, Hex, Kaggle, Hightouch, and Great Expectations further solidify its importance within the data stack. Gable.ai is on track to reshape the data landscape and revolutionize the integration of high-quality data into AI applications.
The success of AI applications relies heavily on the quality of the data being fed into them. Gable.ai’s innovative data collaboration platform and the introduction of data contracts serve as a significant leap forward in ensuring high-quality, reliable, and accurate data for AI systems. The company’s efforts to bridge the gap in data communication and provide an efficient change management system are crucial for the scalability and success of AI. By reshaping the data landscape, Gable.ai has positioned itself as a key player in the data industry, receiving endorsements from prominent founders in the field. With its future prospects, Gable.ai has the potential to transform how AI applications are developed and managed in the years to come.
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