Heavybit Welcomes New Member: Recce

Data pipelines are the New Secret Sauce for every company building with AI, enabling teams to create and improve high-quality training data from their own IP. Recce provides the essential toolkit for unlocking the full value of their data with iteration, refinement, and monitoring, while mitigating the risk of errors and corruption. Heavybit is thrilled to support them as they grow the ecosystem for data pipeline validation in the age of AI as part of our ongoing mission of 10+ years: Bringing critical enterprise infrastructure to market.” - Jesse Robbins, General Partner/Heavybit

The Heavybit team is thrilled to welcome the data validation platform Recce to our portfolio. Recce lets teams validate pre-production data by identifying potentially showstopping data issues before deployment. As a result, teams ship better products faster.

For technical teams, data matters more than ever, particularly as organizations launch and operate AI/ML programs. Teams running AI programs face entirely new challenges, not only in the training and operation of their ML models, but also in managing the datasets they feed into the models themselves.

As it becomes increasingly important for organizations to work with datasets that are complete, correct, and won’t cause downstream problems in production, Recce is saving organizations countless hours of tedious manual data verification before shipping, and countless hours of painful triage post-deploy.

Why We’re Excited

As more teams incorporate data-hungry ML models into their stack, data verification is becoming an increasingly burdensome task. Data teams must spend hours manually sifting through tables to identify potentially critical anomalies, but often lack the full context of why or whether the issues may be significant. They must often draft additional business owners from across the org to verify the severity of the data issues, effectively pulling multiple team members sideways. And if crucial issues do go undetected during manual data reviews and end up in production code, teams must then invest even more resources into those same issues post-launch as those downstream data issues turn into full-blown customer headaches.

Recce deftly solves the “data context problem” by giving data experts full visibility into and context for their data, so they can confidently flag significant data issues to resolve before deployment. As a result, data teams evaluate and approve production-ready datasets in a fraction of the time, technical teams spend less time firefighting in-production data issues, and everyone across the organization can focus on shipping better products and making customers happier.

Going forward, Recce will continue to enhance its platform and scale its team. Learn more about Recce by visiting the website, or start using the open-source version now.

Meet the Founder

CL Kao

Founder and CEO

CL Kao is the founder of Recce. He is a veteran builder who has worked extensively in software, AI, data management, networking, and open source on the CPAN project. He is a board member of Taiwan’s Open Culture Foundation.