Zingle Ai Lab

Data pipelines break. Dashboards drift. Warehouse costs explode. And every data engineer still merges code thinking, “it runs, so it’s fine.” We fix that. We’re building an AI code reviewer made for data engineers - one that deeply understands SQL, dbt, Spark, Snowflake, Databricks, BigQuery, Redshift, and Airflow. Before any change goes live, it reviews your code for: Cost impact - how much it will actually cost in production. Performance - whether it follows best practices for joins, materializations, and incremental loads. Data quality - catching missing or redundant tests, enforcing business logic, and preventing future incidents. Downstream impact - showing what dashboards, models, or metrics will be affected. With every review, it makes your data team smarter - forcing every engineer to think about cost, performance, and reliability before merging. Over time, it turns your tribal practices into automated standards - so your company runs like the world’s best data team. Ship with confidence. Spend wisely. Never break downstream again.