In development. Seeking design partners.

The managed data engineering platform

Data engineering that proves its work.

PillarMesh is being built for small data teams that need to operate sources, a dedicated warehouse, transformations, catalog, dashboards, and evidence as one governed system.

The stack is connected. Accountability is not.

Small data teams often carry source acquisition, warehouse operations, transformations, catalog, dashboards, retries, recovery, and evidence across separate tools. Each boundary creates another place for meaning, state, and responsibility to drift.

Python, SQL, schemas, retries, and backfills are familiar. Spark-style processing, pipelines, and tests are familiar. Reconstructing whether a business outcome was approved, operated, and reconciled should not consume the team.

Planned system

The operating surface, held together.

The planned initial managed warehouse engines are PostgreSQL and ClickHouse.

Operating sequence

Make the work legible from the start.

  1. 01Connect
  2. 02Declare
  3. 03Approve
  4. 04Operate
  5. 05Prove

Contract-first, deterministic, and attributable.

Conceptual

Conceptual execution evidence

A conceptual evidence path: a contract admits a plan, the admitted plan records a run, and the run produces attributable evidence.

A deliberately bounded first scope.

The planned first operating surface covers supported sources, a dedicated PostgreSQL or ClickHouse warehouse, transformations, catalog, dashboards, reconciliation, recovery, and evidence.

PillarMesh is not a general-purpose workflow scheduler, a universal connector layer, or an autonomous authority for meaning and policy.

Bring a real operating constraint.

PillarMesh is seeking small, hands-on data teams willing to examine the planned model against concrete source, warehouse, authority, recovery, and evidence constraints.

Explore design partnership