Architecture Overview

How Stackless is built across sources, warehouse, transformations, semantic models, dashboards, Agent, and operations.

Platform architecture

Stackless is a customer-specific analytics environment that combines managed ingestion, a cloud warehouse, managed transformation models, semantic models, Stackless dashboards, and the Agent.

Business Systems
  -> Source Connectors
  -> Customer Warehouse
  -> Transformation Models
  -> Semantic Models
  -> Dashboards, Agent Artifacts, Exports

The Catalog and Monitor sit across the whole stack. The Catalog gives the Agent and users a searchable map of assets and lineage. Monitor shows operational status for recurring jobs and managed runs.

[picture 1. Stackless architecture diagram from source connectors through Agent artifacts]

Customer environment

Stackless deployments are isolated by customer and environment. A production customer environment has its own application endpoint, authentication configuration, data access settings, warehouse configuration, and operational runtime.

This matters for users because:

  • Your URL, users, roles, dashboards, and data access are scoped to your organization.
  • The Agent only sees data that your role can access.
  • Source configuration and warehouse schemas are managed per environment.
  • Operational actions such as refreshes, publishes, and scheduled exports run in that environment.

Application layer

The Stackless application provides:

  • The Agent conversation UI.
  • Dashboards and the dashboard builder.
  • Data pages for Sources, Catalog, Transformation Models, and Semantic Models.
  • Monitor and scheduled run views.
  • Settings for users, roles, and Agent data access.

Data layer

The data layer includes:

  • Source connector metadata and sync state.
  • Warehouse tables and views.
  • Managed Transformation Model definitions and materialized relations.
  • Semantic Model definitions.
  • Dashboard specifications, versions, published state, and access metadata.
  • Agent conversations, artifacts, uploads, and run events.

Transformation layer

Transformation Models are managed dbt-backed datasets. They use structured specifications instead of arbitrary one-off SQL for most common business reporting needs. The managed spec supports filters, joins, aggregations, unions, flattening, dedupe, windows, pivots, unpivots, tests, and refresh policy metadata.

When a request does not fit a managed operation, the Agent can identify that limitation and route the work to a raw dbt or implementation review path.

Semantic layer

Semantic Models define measures, dimensions, joins, and business names. They are the layer dashboards and Agent charting use to make a metric mean the same thing everywhere.

Semantic Models should usually reference published Transformation Models, especially when the business logic includes cleaned fields, enriched joins, dedupe, attribution, or custom metric rules.

Dashboard layer

Stackless dashboards are native dashboard artifacts. They can be private drafts or published organization dashboards. The dashboard system supports version history, forks for editing published dashboards, filters, tabs, charts, KPI cards, tables, metric definitions, scheduled exports, and Agent-assisted edits.

Agent layer

The Agent can:

  • Search the Catalog.
  • Inspect dashboards, models, metrics, and lineage.
  • Run read-only warehouse analysis within access limits.
  • Create briefs, findings, table artifacts, and chart cards.
  • Build or edit private dashboards.
  • Draft Transformation Models and Semantic Models.
  • Help prepare publish, refresh, or downstream-impact workflows.

The Agent is built to produce durable outputs, not just temporary chat answers.

Operations layer

Monitor, run history, refresh status, and Agent run events provide visibility into operational work. If a model is stale, a publish is still running, a source needs attention, or a dashboard export fails, the operational layer is where the status should be checked.

Security model

Stackless uses authentication, role-based permissions, dashboard access rules, and schema-level Agent data access to control what users and the Agent can see or change. See Security and Access for details.