Over the past decade, companies like Snowflake, Databricks and DBT have all pioneered new data primitives. These building blocks have addressed the hardest challenges in data management, processing and transformation to harness enterprise data for analytics or machine learning use-cases. Their success stemmed from a couple of factors. Firstly, they entered the market at a time when organizations were increasingly looking to modernize their data infrastructure to take advantage of market tailwinds around cloud adoption and big-data. Secondly, they were committed to embracing simplicity. Lastly, they empowered data practitioners while seamlessly fitting into their workflows.
Today a new set of forces are driving the need for reimagining the existing data stack. The headwinds caused by the growing cost of centralizing data and the complexity of reverse engineering high quality data; and the tailwinds of AI/ML that are forcing every enterprise to become AI-first.
Gable’s founders, Chad Sanderson, Adrian Kreuziger, and Daniel Dicker, faced these pain-points at Convoy, the $4B digital freight network, where they were responsible for the entire data stack. Chad conceived of a net new data primitive - “data contracts”, which brings data producers and consumers together around the management and enforcement of constraints on upstream data assets for the benefit of downstream data products. Data contracts helped merge SWE, data engineers, and ML/BI silos to ensure that Convoy’s production data met its needs for analytics and AI/ML purposes. During their time at Convoy, the team implemented dozens of data contracts that resulted in meaningful ROI for the company.
Fast forward to today, Gable aims to bridge the gap between software developers and data teams. In software engineering, this problem is addressed through systems like GitHub that enables software engineers to to directly subscribe to repos they care about, ensuring changes are communicated to teams that will be impacted as a result.
Companies are beginning to realize that there is a critical piece missing in today's data workflows — software engineers don't understand the use cases for the data they're collecting.
As a result, critical data is missing, lacks semantic context, or is modeled poorly. There’s needless duplication, no sense of ownership, and pipelines break in production. Gable’s data communication, collaboration and change management platform is reimagining the data workflow. The primitive building block for Gable is the data contract, which can be defined by data platform teams, data engineers or analytics engineers. These published contracts can be implemented by adding checks in CI/CD to prevent changes in repos that violate the contract. Subsequently, Gable can offer remediation/actions to address the severity of the violation. This empowers data engineers to no longer need to be reactive to pipelines breaking in production.
Along the way, Chad has demonstrated the unique power of community building through his evangelism efforts and discourse on the emerging practices in data/AI. Chad has real mindshare as shown by Data Quality Camp, a slack group of 8000+ data practitioners that he started just 8 months ago, or his growing list of 11000 Substack subscribers. His audience has validated that the problems he solved with data contracts were not limited to logistics; they were essentially universal. This expert community of data and ML practitioners has been integral in designing Gable.ai’s platform to solve real market pain points.
To build this company, Chad, Adrian and Daniel have assembled a stellar team from organizations like Convoy, Amplitude, Google, Twitch, Reddit, Shopify and many others. Zetta was proud to lead Gable’s $7M seed round alongside Scott and Krishna from Crane Ventures, Timothy Chen from Essence VC, Allison Pickens from The New Normal Fund and prominent data angels that include the founders of dbt Labs, Monte Carlo, Kaggle, and Great Expectations.
In the same way that GitHub is essentially a default choice when it comes to software development, now that Gable’s out in the open I expect its platform to be seen as obvious and nearly essential for any enterprise implementing end-to-end data workflows for any purpose including business intelligence, ML, or AI applications.
It’s not just a new company; it’s a new category!