Value proposition

Who Beneath is for and what problems it solves

Beneath is a full, transparent and stable data system in-a-box. Its aim is to make it as easy as possible to turn good ad-hoc data science into good data-driven products and services.

Ordinary data engineering tasks consume too much time

As data scientists and data engineers, we want to spend our time on the unique things – like developing models and creating an intuitive user experience for our insights. But all too often, our time is consumed by the increasingly complicated task of coordinating schemas, integrating data sources, and managing infrastructure.

Data system in-a-box

Beneath bundles a variety of useful systems and features characteristic of modern data systems. These include systems for log streaming and replay, low-latency indexed lookups, and analytical data warehouse queries. And useful features for deriving new streams, running transformations, and sharing streams with partners or the public. Basically, it helps you to not reinvent the wheel every time you start a new data project.

Your entry point to Beneath is the Console, a user interface that gives you a single overview of your streams and how they tie together. From the Console, you can monitor your data in real-time, see who has access, and get a long list of integrations, which span REST and Websocket APIs, Python and JavaScript libraries, and most modern business intelligence software (through BigQuery).

Who is Beneath for?

Beneath is for any project that wants to deliver more data-driven features. It especially shines if:

  • You have a cool ad-hoc data project that you want to put into production (e.g. to keep the results updated in real-time or to integrate it into a product)
  • Your data infrastructure and pipelines increasingly consume valuable engineering time that you would rather spend differently
  • You’re looking for a tool to help you break down data silos and make it easier to share and collaborate on data with external partners or the public