The use cases we're trying to solve are:

- Production-like data in development environments

- Improve incident handling by masking all data that is not relevant

- Share a subset of your data

- Protecting data being shipped into a data lake

- Safe data to expose in internal tooling, metrics, or BI dashboards

- Empower non-technical staff to vibe-code against sanitized data

# How it fits in your stack

- Role based policies: define masking rules in our web dashboard

- The proxy picks up the configuration and starts applying rules automatically.

## You host it

- it's a docker container, two environment variables: an api key, and the database URI connection

## We host it

- Drop-in proxy: no code changes. Point your connection string at a new endpoint, that's it.

# How it works (and how fast it is)

Restructuring the query AST based on the config. AST rewrites depend on the text/structure of the query, not on how many rows the database eventually returns, so they are effectively O(1) with respect to result size.

# Status & feedback wanted

VeilStream is GA, but billing isn’t switched on yet so it's currently free at all tiers. We’d love your thoughts on:

- throughput / latency in real workloads

- Filter rules & DevX

- weird edge-case queries (pg_dump, logical replication, etc.)

I’ll be around all day to answer questions and dig into issues.

# tagline

Ship features with data you can trust and privacy you don't have to worry about.