I work at a product team in a relatively large SW company. To continuously improve the product experience, we wanted to get more complex insights out of the data. Because we were not getting it from enterprise solutions such as Google Analytics, we decided to build a data pipeline and tools for data analytics for the company.

While building it for ourselves with a great team (data engineers, DevOps), I learnt that such internal product is only affordable for large tech companies who have the resources to ramp up their own team of experienced people. With some market research, I came to the conclusion that there is a need for a lightweight and relatively cheap SaaS for small and medium sized teams to offer data services.

Right now, I have teamed up with a friend to see if we can build a SaaS business around the problem. We are currently engaged in building an MVP and validating the idea. The MVP shall offer some of these

- An API for reporting product logs

- An infrastructure to collect and process product logs

- A service to access the raw data for exploratory analysis

- A service to govern the data (validation, privacy, etc)

- A service to manage A/B experiments

- A service to manage ML models.

- A marketplace for third-party add-on services to work with data

In short, we want to offer services that helps small teams with one or two people capable of working with the data (through pandas, NumPy or Spark) can easily gain deep insights about their products without going through hassles around data infrastructure and data tools.

The current market segment we want to focus is mobile app (Android, iOS) makers.

At this point of time, we are looking for evidence that proves or disproves our idea. We are also looking for early adopters who are willing to use our MVP and give us feedback.

I would deeply appreciate if the HN community can give us any feedback / insights on the above stated topic.