Anyone working in data management and data science can attest to the challenge and time-consuming nature of mapping a set of data from a new source into a platform where it can be cleaned, validated, and ultimately analyzed and used to train algorithms. After all, your algorithms are only as good as the data used to train them. Now imagine if these data sets are coming from hundreds of external users who have employed any number of systems to collect this data, from Excel files to actual shoeboxes full of photos. That is the challenge that non-profit wildlife conservation machine learning and artificial intelligence service provider Wild Me has faced over its more than a decade of operation. The organization builds open software and AI for the conservation research community.

David Boskovic was excited to join a company called Envoy back in 2016. He had worked with B2B startups since he was 18, and was looking forward to helping another tech startup scale an idea. But that excitement turned to dread when Boskovic realized his first job was to build yet another data onboarding system. "Eric [Crane] was leading product I was leading engineering, and for the umpteenth time in our careers, we had to build this CSV data onboarding solution for yet another SaaS company," Boskovic said. Envoy needed a painless way for new customers to move their existing data into its new SaaS offering so that it can do interesting things with it.