Flow

Governed transformation for the Gold layer

Governed transformation automation for the Gold layer

Flow is the data transformation layer — bringing governed, model-driven automation to the Gold layer of the Medallion architecture.

The Problem

The Gold layer is where complexity concentrates

While ingestion and raw processing are commoditized, complexity, duplication, and risk concentrate in the Gold layer. As analytics scale, logic fragments, transformations drift, schema changes cascade, and governance weakens.

Manual rework slows delivery

Schema changes require repeated fixes across downstream assets.

Manual rework slows delivery

Schema changes require repeated fixes across downstream assets.

Transformation drift creates risk

Gold-layer logic diverges from upstream models and intended semantics.

Transformation drift creates risk

Gold-layer logic diverges from upstream models and intended semantics.

Duplicated logic increases cost

Business rules are reimplemented across SQL, dbt models, and YAML.

Duplicated logic increases cost

Business rules are reimplemented across SQL, dbt models, and YAML.

Ownership and intent get lost

Code-first approaches scale execution, but not governance or traceability.

Ownership and intent get lost

Code-first approaches scale execution, but not governance or traceability.

The Solution

Introducing Flow

Flow is a visual, model-driven environment for designing, governing, and reusing transformation logic in the Gold layer — bringing structured automation and control to where complexity concentrates.

How It Works

From design to governed execution

Visual transformation design

Transformations are defined using a graphical mapping builder that makes logic explicit, reviewable, and understandable.

Abstract mappings for reuse

Governed metadata and versioning

Deterministic code generation

Open execution model

Visual transformation design

Transformations are defined using a graphical mapping builder that makes logic explicit, reviewable, and understandable.

Abstract mappings for reuse

When logic becomes repeatable, it is promoted to an abstract mapping and reused across multiple datasets, eliminating copy-paste patterns.

Governed metadata and versioning

Every mapping, pipeline, and release is versioned, traceable, and governed as part of the VaultSpeed metadata foundation.

Deterministic code generation

Execution code is generated consistently from governed metadata and templates — not manually rewritten.

Open execution model

Generated code runs in your chosen execution environment (dbt, Snowflake, Databricks, BigQuery, Synapse) — without a VaultSpeed runtime.

The Difference

Governed automation by design

Built for the agentic enterprise

VaultSpeed’s governed Medallion architecture provides grounding through high-quality data and rich, structured metadata — giving AI agents reliable context to operate safely and deterministically.