Why we're building DataAstra
The problem we're solving
Data engineers spend 40% of their time debugging pipelines that failed because a column was renamed, a schema changed, or an AI-generated query referenced a table that doesn't exist. None of these failures are inevitable. They're the result of building data infrastructure without a type system.
Every existing platform treats data pipelines as configuration files or scripts. Great Expectations checks quality after the fact. dbt has lineage as metadata, not a compile-time guarantee. Dagster orchestrates but doesn't understand schemas. And AI is bolted on top of all of them as a text generator — not as a verified compiler.
DataAstra is the first platform where pipelines compile. Where lineage is a proof, not a post-hoc annotation. Where AI generates into a type system and the compiler catches hallucinations before they become incidents.
How we build
We will never ship a feature that makes the platform less deterministic. Performance is table stakes. Correctness is the product.
Your data stays in your infrastructure — Snowflake, Databricks, PostgreSQL, S3. DataAstra manages it without moving it. Zero vendor lock-in on the storage layer.
AI isn't a chatbot we've added. It's the authoring engine, the review agent, the documentation writer, and the on-call assistant. It runs the platform.
The company
DataAstra is a product of Cognitive Tech Labs LLC, founded by data infrastructure engineers who spent a decade building and operating data platforms at scale.
We're building the platform we wished existed — one that treats data pipelines as compiled programs, not glue code. One where the AI generates into a type system instead of a text box. One where lineage is a proof, quality is a language construct, and the cognitive engine handles incidents autonomously.
We're based in the United States and currently in the pre-seed stage, building toward our first design partner deployments.
Interested in what we're building?
We're looking for data teams that want to be early adopters. Book a demo and let's talk about your data challenges.