We are a seed-stage startup that wants to build a more thoughtful world.
There is a lot of buzz around "data" but we are skeptical that data in of itself is valuable or more data is always better or data is sentient like "the data will tell us"- instead, we, as users, need to provide the shape and context to convert data observations into the right interpretations. Second, this obsession over data itself, has led to a derived obsession around base-level tooling, democratization, and self-serve of data - "data for you, data for you, data for everyone" (pretty hard to argue against democracy!) but we are also skeptical that barring the few folks who wrestle with data for a living day in and day out (and enjoy it!), what most people really want is access to an abstraction that is business-speak, domain-speak - not tables, fields, columns etc. And they want ways to participate and contribute as well.
We believe, drawing heavily from our personal experiences and first principles, that there is a new, different way to provide structure over data that in turn provides enormous leverage for organizations - a source for metrics, dependencies between metrics, between metrics and their dimensional attributes and causal drivers - an unified metrics layer that can power the next generation of data-led operational cultures.
As dual producers and consumers of data artifacts, we want to help the analysts, data scientists, and analytical operators, who toil day-to-day with increasing volumes of observational data inside a swamp of tables, code, and dashboards, and are asked to weave magic. We want to ease their day to day cognitive burden, promote hygiene and productivity - where not only are they building on each other's work with the right lego blocks - they are also not doing tedious wasted work reconciling why outputs are different across different users, use cases or teams.
For strictly consumers of data artifacts, we believe this metrics layer hits the right sweet spot of what most people need in an organization - clean interfaces to navigate key metrics and their dependencies, track not just the what but easily explore and answer the "why" questions. We imagine a world where a suite of data applications can be built on this metrics layer that balances the perpetual tension between flexibility ("want more data shapes") and reliability ("but accurate and reliable"), and allows organizations to be more in flow.
We are recently funded by top tier VCs (FirstMark and Amplify) and angels in the data/dev tooling space.
Our founding team is exceptional with lived experiences in scaling high-growth startups (Uber, Rent the Runway) and want to take our learning to dream, shape and will into reality a new category of enterprise software. If you have ever wanted to join on the ground floor of a well-funded deep data/dev startup with fertile engineering and product challenges, this is it!