Curiosity - 2026 Pricing, Features, Reviews & Alternatives

AI grounded in industrial context.

Curiosity is the context graph for industrial AI. It connects records that live in separate systems into one typed, permission-aware knowledge graph: tickets, part and BOM data, maintenance logs, supplier notices, field reports, email, SharePoint, Jira, Confluence. People and the language model you choose get that context.

Curiosity Studio is the product. Write a sentence, for example ""Build a supplier-risk review for the A320 line"", and Studio builds a working internal tool on your connected data: an app, a dashboard or an agent.

Prompt-to-app is easy. Prompt-to-app that a regulator would accept is not. The hard part was never the interface. It is the data, the permissions and the proof.

Four differences:

1. Grounded, not guessed. Built on the graph, so every output traces back to a record.

2. Your permissions, inherited. A generated tool cannot show anyone something the source system would not already show them.

3. From prompt to production. It ships to real users, with an audit trail.

4. Runs on your infrastructure. Your environment, your model.

Underneath them: graph, search and AI are one system, not three products joined together. Permissions are checked when the question is asked, synced from the source systems, down to the single record. Any model, on your servers: OpenAI, Anthropic, Mistral, Meta or local models, on premises or in a private cloud. Curiosity is not the model. It is what gives the model context.

In production: 30TB+ of connected data, 20,000+ active users across deployments, 15%+ efficiency gain in production workflows, 70+ integrations with enterprise systems. Reference customer: Airbus (Airline Services, Services Innovation Team).

Built in Munich. GDPR, EU data residency, on premises or private cloud. Full member of the KI Bundesverband.