curiosity

Comparison · Industrial AI

Curiosity and AVEVA and Cognite
Operational data, or the whole record

Curiosity connects every industrial record; AVEVA and Cognite contextualize operational data.

Their deployment Vendor cloud Their data model Industrial knowledge graph of assets Our deployment Cloud or your own servers Our residency EU, or your own

Your data · your environment

Who each tool is for

Different problems, honestly stated

Curiosity

For industrial and regulated teams whose knowledge sits in engineering systems and structured records, where the answer depends on how those records connect, and where the deployment has to run on their own infrastructure.

AVEVA and Cognite

Cognite Data Fusion is an industrial DataOps platform with a knowledge graph of assets, time series, events, documents and 3D models, and Atlas AI for building agents on it. Schneider Electric agreed in June 2026 to acquire Cognite and combine it with AVEVA, its industrial software business. Both are strong in energy, utilities and process industries, delivered mainly as cloud services.

How Curiosity compares

Where the boundary falls

Cognite and AVEVA are very good at putting sensor and asset data in context. Curiosity is broader in what it connects (tickets, supplier notices, email, engineering change orders), runs on your own infrastructure and sits outside any one automation vendor.

Every record, not only plant data

Sensor and asset data tell you what happened. The tickets, part records, supplier notices and field reports around them tell you why. Curiosity joins both.

Across vendors, not inside one

A plant runs systems from many suppliers. Curiosity connects them into one graph rather than adding intelligence to one vendor’s applications.

Tools your teams describe

Studio builds the app, dashboard or agent from a sentence, on the connected data, so a new tool is not a new project.

Side by side

Feature comparison

The same five questions, answered for both.

QuestionCuriosityAVEVA and Cognite

Deployment

Cloud or self-hosted, ready to use

Vendor cloud

Data model

Managed context layer and knowledge graph

Industrial knowledge graph of assets

Industrial fit

Built for industrial and enterprise teams

Energy, utilities, process industries

Data reach

70+ systems connected, and yours through a connector you write

OT, IT and engineering data

Residency

EU hosted, or entirely your own infrastructure

Vendor cloud regions

Customization

What your team can change

Your own code, interface, data model and configuration. AVEVA and Cognite as its own documentation described it in October 2026. Where it says Not available, the vendor documents no such capability.

QuestionCuriosityAVEVA and Cognite

Your own code

C# endpoints, AI tools and tasks, compiled in Studio

Python in Cognite Functions, hosted in CDF

Your own interface

Your own front end in C#, deployed from git

Flows React custom apps, Streamlit apps, Canvas

Data model

Typed node and edge schemas you define

Containers, views and data models, property graph

Configuration as code

Every change committed to git, pushed to your remote

Cognite Toolkit YAML modules, CI/CD pipelines

APIs and SDKs

REST API, C# and Python library, connector SDK

REST API, Python and JavaScript SDKs

AI integration

What AI can build and reach

Whether AI can build on it, who reviews the result, and which models it runs. AVEVA and Cognite as its own documentation described it in October 2026.

QuestionCuriosityAVEVA and Cognite

AI that builds

Sudo drafts endpoints, tools, schemas and screens

Builder skills guide coding agents through Flows apps

Review before it applies

Every change a diff a person approves, in a sandbox

Apps deploy as drafts, then signing and certification

Model choice

Any major provider, or an OpenAI compatible endpoint

Azure OpenAI, Google and AWS models by region

Models on your servers

Open weights on your servers, or air gapped

Not available

Assistant permissions

Built in tools search as the user, per record

Industrial MCP uses the signed in user's permissions

Agent protocols

MCP server and an OpenAI compatible API

Industrial MCP server for MCP clients

At Airbus, we developed the next generation of customer support AI assistance tools with Curiosity, enhancing our technical support’s ability to access and navigate vast data from multiple sources, including millions of documents.

Services Innovation Team

Airline Services at Airbus

Your data. Your infrastructure.

Connected knowledge for AI systems