Integrations · Cognite Data Fusion
In progressCognite Data Fusion integration.
Cognite Data Fusion contextualizes industrial data across assets, time-series, documents, and 3D models. The engineering graph Armeta produces from P&IDs is a natural contextualization source — asset hierarchy, drawing references, and cross-drawing connectivity, structured for ingestion.
By Armeta Engineering Team, Engineering Team
Last reviewed:
Draft in progress
This page is currently being written. The scope and framing are locked; the full technical write-up is on the editorial calendar. If this page is directly relevant to an active evaluation, the Armeta team can walk through the content with you live.
What this page will cover
- 01What Cognite Data Fusion does in this context — the CDF data model, asset and document contextualization, and how engineering data anchors other industrial data sources.
- 02What structured P&ID data looks like in CDF — assets, relationships, files, events, and how the Armeta engineering graph maps into each.
- 03How Armeta's output maps to the CDF schema — asset typing, relationship definitions, file references to the source drawing, and the attribute set Cognite applications expect.
- 04Integration pattern — JSON output aligned with the CDF Python or REST SDK, batch ingestion for archives, or event-driven updates tied to drawing revisions.
- 05Implementation approach and typical timeline — discovery of the CDF data model, mapping of Armeta object types to CDF asset classes, pilot ingestion, then broader rollout.
- 06Case considerations — existing CDF maturity, integration with Cognite's 3D and document contextualization features, and the governance of asset model changes.
Your drawings, your data
Start with ten of your own drawings.
Reference pages describe what Armeta does. The fastest way to know what it does for your team is to run it on your actual P&IDs.