Zingg Turns Two!

The days were long, but the years have been short.

Two years is a journey, yet it seems like yesterday when I open sourced Zingg. In the interim, we have done fulfilling work and received a lot of love. Curious what’s up at our end? Read on!

First thing first.

We now have paying customers for our enterprise products! There is nothing more exhilarating than seeing our life’s work come alive. And to be paid so that we can continue to build and move in the direction we aspire to. In the startup world, we hold a lot of discussions around product market fit, product founder fit, building things people want, user research, and other associated activities. Product-led startups like ours get the first set of customers through the urgent need of a visionary early adopter. The visionary early adopter is the person in a team who has a pressing need along with the foresight to solve the problem and the confidence to trust a new team and an innovative product. And who can influence and move budgets to solve that need. I am very glad to have this opportunity to work closely with this first set of customers who are helping us shape the product. Not just the features, but also the pricing.

Thank you for supporting us so that we can help you!

We are building three flavors of Zingg Enterprise. Zingg Snowflake, Zingg Databricks and Zingg Spark. All of them with the same roots in Zingg open source. Each carries forward Zingg OSS and gives the required ammunition to build and use the persistent and evolving enterprise identity graph. Zingg Enterprise creates global unique identifiers for entities, explains model behaviour and maintains and enhances the identity graph through resolution of new and updated records against previously matched records. Of course there is the improved accuracy and scalability :-)

On top of this, we have added platform-specific features. The Snowflake version runs inside Snowflake without any other infrastructure or software dependence. The Databricks flavour adds Unity Catalog support and a lot of other Databricks goodies. The Spark one has the enterprise features and runs on all other Spark environments like EMR.

On the open source side, we just hit 1000 downloads per month on PyPi! The rate of downloads has doubled over the past few months, and we now have a Slack group touching 450 people, from varied organizations like LinkedIn, Maersk, Newfront, Samba TV, Canadian Football League, Heb and John Deere to name a few. We have federal agencies like Pandemic Response Centre, and established startups like Provenance.org, Redica Systems, Ninjacart and Cherre. We have a good number of nonprofits and data consultancies as well as friends from Databricks, Snowflake and Exasol. The strong code contributions from these partner companies have helped us to support their users more deeply.

We are clearly onto something :-)

I am truly amazed by the depth of use cases we are seeing across big and small organizations in varying domains. Zingg is resolving customer identity for marketing and personalization use cases in retail. It is resolving patient identity for comprehensive health, and healthcare provider identity to understand drug recommendation patterns. And the identity of an insurance policyholder, for compliance and risk, and also from the point of view of a reinsurer. Identity resolution is much broader than we thought initially. It is the identity of members of religious establishments, of donors or recipients. It is the identity of the fans of a football club to send out the right information at the right time for a game of their liking. B2B accounts, which buy from multiple subsidiaries in different geographies, need identity resolution as well. So do products on an e-commerce website for competitive analysis on other sites.

Identity is anything and everything a business cares about.

We are happy that we built Zingg so that users can work on their schema and train on their data without specialized ML skills. All in a privacy centric way. This has allowed us to see Zingg in action in the different use cases we are discovering every passing day.

To each of you who has used Zingg, mentioned us to friends and coworkers or checked us out - thank you for your time and we hope we have removed some data troubles from your life.

I also wanted to thank our investors and advisors, who backed Zingg when no one had heard of us, and who have been generous with their time and support.

These two years have been a tremendous learning experience, and our plans are only getting bigger. There is a lot of AI yet to be applied to enterprise data, and we will love to create more value for our users and customers. For that, we need to continue to work closely with them, ship more and more often, keep the momentum going and work twice as hard.

We are excited for the path ahead. Wish us luck!