curiosity

Comparison · App and agent builders

Curiosity and ServiceNow and Moveworks
The workflow, or the knowledge behind it

Curiosity builds tools on engineering knowledge; ServiceNow and Moveworks build agents on service workflows.

Their deployment Vendor cloud Their data model Agents on service workflows 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.

ServiceNow and Moveworks

AI agents and an agent builder on the ServiceNow AI Platform, acting on IT, HR and customer service workflows, with Moveworks’ assistant for employee requests since ServiceNow acquired it in December 2025. They work best where the process already runs in ServiceNow.

How Curiosity compares

Where the boundary falls

ServiceNow agents move a ticket through its workflow, and Moveworks resolves the recurring employee request. Studio answers what the ticket is about, from the part records, maintenance logs and field reports kept in other systems. Both can reasonably exist in the same organization.

Grounded, not guessed

A tool Studio builds runs on the graph, so every figure it shows traces back to a record in a source system.

Your permissions, inherited

A generated tool cannot show a user anything the source system would not already show them, down to the individual record.

From prompt to production

The tool ships to real users with an audit trail, not as a prototype someone has to rebuild before it goes live.

Runs on your infrastructure

On premises or in your private cloud, with the language model you choose.

Side by side

Feature comparison

The same five questions, answered for both.

QuestionCuriosityServiceNow and Moveworks

Deployment

Cloud or self-hosted, ready to use

Vendor cloud

Data model

Managed context layer and knowledge graph

Agents on service workflows

Industrial fit

Built for industrial and enterprise teams

IT, HR and customer service

Data reach

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

ServiceNow and its integrations

Residency

EU hosted, or entirely your own infrastructure

Vendor regions

Customization

What your team can change

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

QuestionCuriosityServiceNow and Moveworks

Your own code

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

JavaScript and TypeScript server code on the instance

Your own interface

Your own front end in C#, deployed from git

UI Builder, UI pages and custom components

Data model

Typed node and edge schemas you define

Tables, fields and relationships you define

Configuration as code

Every change committed to git, pushed to your remote

Git in ServiceNow IDE and SDK, CI/CD APIs

APIs and SDKs

REST API, C# and Python library, connector SDK

REST APIs, ServiceNow SDK and Fluent

AI integration

What AI can build and reach

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

QuestionCuriosityServiceNow and Moveworks

AI that builds

Sudo drafts endpoints, tools, schemas and screens

Build Agent generates apps from a prompt

Review before it applies

Every change a diff a person approves, in a sandbox

Plan approval and code preview before build and install

Model choice

Any major provider, or an OpenAI compatible endpoint

Azure OpenAI, Google Vertex, generic LLM connector

Models on your servers

Open weights on your servers, or air gapped

Now Assist on self hosted instances, by support case

Assistant permissions

Built in tools search as the user, per record

Dynamic user inherits the invoker's roles, or AI user

Agent protocols

MCP server and an OpenAI compatible API

MCP server, MCP client, A2A 0.3

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