Pipelines that run themselves

What we build

The backbone for operations-heavy businesses: ELT and streaming pipelines that handle data from thousands of rows up to billions — and the bidirectional CRM ↔ operational-DB sync that keeps HubSpot data live inside the applications that need it.

What good pipelines look like

flowchart LR
    A[Sources] --> B[Snowflake / BigQuery]
    B --> C[DBT transformations]
    C --> D[Downstream apps & BI]
    E[Streams: Kafka / Pub-Sub] --> C

Orchestrated by Airflow or Dagster, observed end-to-end, and tested before each release.

HubSpot ↔ PostgreSQL, in real time

For clients running HubSpot as the system of record, we wire it bidirectionally to PostgreSQL via Stacksync. Sales reps see fresh operational data inside HubSpot; the operational app reads CRM context from its own database. No nightly batch lag.