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Curiosity Studio

Describe the tool.
Get the software.

Studio builds internal apps, dashboards and agents from a description, on your connected data, in your environment, ready for real users rather than a demo.

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A description becoming a running internal tool A written request passes into Studio and comes out as an application with a chart, a result list and the source records each answer was drawn from. Every open quality issue traced to a supplier STUDIO Quality issues by supplier BY PLANT Supplier ASupplier BSupplier C SOURCES TICKETNOTICEREPORT
A description becoming a running internal tool A written request passes into Studio and becomes a working application, standing on tickets, part data and supplier notices. STUDIO Supplier risk BY PLANT YOUR GRAPH Tickets Part data Supplier notices

Trusted in complex environments

How it is used

One system, several jobs

The same graph serves the search box, the agents and the tools your teams build in Studio.

01

Ask across everything

One question against every connected system, answered with the record it came from.

02

Build tools on it

Studio turns a description into an internal app on the same graph and the same permissions.

03

Run agents against it

Agents get typed context and an audit trail rather than a scraped text dump.

04

Feed your own code

REST and C# SDKs when you would rather build it yourself.

What Studio stands on

Everything you need to build enterprise AI on your data

Instead of stitching a graph database to a search engine to a model gateway and maintaining the seams, the pieces ship as one system that already agrees with itself.

For developers

Typed knowledge graph

Model entities and relationships, not just documents. An aircraft has components. A component has bulletins and a supplier.

Hybrid retrieval

Keyword, vector and graph traversal in one query, so precision and recall stop being a trade you have to pick.

Permission-aware answers

Access is synced from the source systems and enforced at query time, down to the individual record.

Any model

Commercial APIs or local weights. Curiosity is not the model. It is what gives the model context.

70+ connectors

SharePoint, Outlook, Teams, Slack, Confluence, Jira, S3 and SQL. Records stay where they live.

In memory at scale

Interactive query times across tens of terabytes, so the graph is something people actually use.

One runtime

Graph, search and AI in one system

Connect data across systems and structure it so both people and models can work on it. One runtime, one permission model, one place where the context lives.

  • The models you choose, on top
  • Hybrid retrieval beneath them
  • The context graph under both, inside one permission boundary
Graph, retrieval and models in one runtime Three stacked layers inside a single frame: the language model of your choice on top, hybrid retrieval beneath it, and a graph of connected records underneath both, with one permission boundary around all three. ONE DEPLOYABLE · ONE PERMISSION BOUNDARY Models you chooseOpenAIAnthropicMetaLocal Hybrid retrievalKeywordVectorGraph walk Context graph
Models, retrieval and the graph in one runtime Three stacked layers inside one frame: the models you choose, hybrid retrieval beneath them, and the context graph they both stand on. ONE DEPLOYABLE Models you chooseHostedLocalHybrid retrievalKeywordVectorContext graphRecordsLinks

Structure

Model the data you actually have

Industrial data is not a pile of documents. It is parts, revisions, serial numbers, obligations and the relationships between them, and flattening it to text throws away the part that matters.

  • Entities and typed relationships across systems
  • Structured records alongside free text
  • Revisions and history kept, not collapsed
Records across systems joined into one typed graph Four source systems on the left feed a central aircraft record, which is joined by typed relationships to a component, a bulletin and a supplier, rather than by shared keywords. TicketsPart dataSupplier noticesField reports A320 ComponentBulletinSupplier TYPED RELATIONSHIPS, NOT KEYWORDS
Records from separate systems joined into one typed graph Three source systems feed a central aircraft record, which is linked by typed relationships to a component, a bulletin and a supplier. TicketsPart dataSupplier notices A320 Component Bulletin Supplier TYPED RELATIONSHIPS

Connect

Connect everything. Replace nothing.

Curiosity reads from the systems you already run and leaves the records where they are. No migration project, no second source of truth to keep in step.

  • Records stay in the system that owns them
  • Permissions read from the source at query time
  • Incremental sync, not a nightly rebuild
Source systems connected around one core Eight enterprise systems arranged around a central context graph, each linked to it, with records staying in the system that owns them. SharePointConfluenceTeamsS3 OutlookJiraSlackSQL Context graph
Source systems connected around one core Four enterprise systems arranged around a central context graph, each linked to it, with records staying in the system that owns them. SharePoint Outlook Jira SQL Context graph AND 70+ MORE

Why this is different

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.

01

Grounded, not guessed

Every tool is built on the graph, so what it shows traces back to the record it came from.

02

Your permissions, inherited

Generated tools cannot show a user anything the source systems would not already show them.

03

From prompt to production

What Studio builds ships to real users with an audit trail, not to a sandbox that dies on Friday.

04

Runs on your infrastructure

On premises or in your private cloud, with the model you choose. Your data does not leave your environment.

What you can build

Tools teams build first

Once building one stops being a project, the backlog empties in a different order.

Review dashboards

A live view of open issues across plants, suppliers or programs, each figure traceable to its records.

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Triage assistants

Case routing that already knows the part, the history and what fixed it last time.

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Change reviews

Every open engineering change order on a program, with the parts and documents it touches.

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Obligation trackers

Contract and compliance deadlines pulled out of documents and watched, with the clause attached.

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Research agents

Long-running questions across the estate, returning a written answer and the chain it followed.

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Security

Built for security

Made in Germany and built for data sovereignty. Your data stays in your environment, encrypted and access controlled down to the individual record.

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On premises or private cloud

Deploy on your own infrastructure or in certified data centers in Europe.

Single sign on and enforced MFA

Access synced to your data sources with relationship based permissions.

Full audit trail

Every query, download and data access logged.

Data residency

Your data stays in the region you choose.

Made in Germany

Built in Munich.

GDPR compliant

European data protection standards.

Your data. Your infrastructure.

Describe it on Monday.
Ship it this week.

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