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Two plans. The developer version is free for up to ten test users, with no time limit for development use. Enterprise Studio is priced for your deployment, on your own infrastructure, starting from fifty users. See Pricing.

Yes. The connector SDK brings custom sources such as a DMS, an ERP or a CRM system into the same graph as the built in connectors, with their records, relationships and permissions. See Extensibility.

Yes. The records and files you map are copied into Studio and kept in step by the connector. The source system stays the system of record, and each node links back to it.

Where a source has permissions, Curiosity syncs them, so a person only sees what the source system would show them. A change in the source reaches Curiosity with the next sync. For a source without permissions, such as an S3 bucket, you choose who may see it when you connect it. See Security.

In the browser, at an internal address you host, inside the environment your organization already has. Teams can also reach it from the command line, or through MCP from their own agents.

Yes. Point Studio at any endpoint that speaks the OpenAI API, or write a provider of your own in C# inside Studio for any other API. That covers most inference servers for open weights, the gateways platform teams run, and the cloud endpoints the major providers offer in your region.

Yes. OpenRouter is one of the providers built into Studio, so one key reaches every model it lists, and you can limit which upstream providers it routes to. Requests to OpenRouter leave your environment, so keep it to data that may go to a hosted model.

Yes. The model is a setting of the provider, so changing it is configuration. The graph, the permissions and the tools your teams built do not change with it.

Open weight models, run on your own servers: 15 in the list above, from OpenAI, Google, Mistral, Meta and Microsoft. Nothing is sent to a provider. Ask us which fit the hardware you plan to deploy on.

Yes. Run open weights with Ollama, or with any inference server that speaks the OpenAI API, on your own hardware. Studio calls it like any hosted provider.

No. Permissions are resolved at query time, before the model is called, so Studio's built in tools only hand the model records the person asking may see. Tools you write in C# get a query scoped to that user too: use it.

In the cloud, traffic runs over TLS 1.2 or later and your data is encrypted at rest with AES-256. On premises you hold the encryption key and the certificate. Access follows the permissions of your source systems, down to the record, and activity can be logged. The controls page lists every control.

An on premises deployment stores your data in your environment, and Curiosity holds none of it. A cloud deployment stores it in an isolated tenant in European data centers.

No. Customer data is never used to train shared or public AI models.

On premises, your records go only where you send them, and with a local model no AI provider sees them. Product usage, with each user's name and email address, goes to Mixpanel, and error reports go to Curiosity's own server until you switch them off. In the cloud, a language model sees the chats and referenced content a user sends it, temporarily and private to that user. OpenAI is the optional default, and you can choose another model. The subprocessors page lists everyone else.

Where you deploy. On premises it stays in your environment, and with an offline license it can run air gapped. Cloud deployments run on Hetzner, in Europe.

Cloud deployments use TLS 1.2 or later, and the graph and your files are encrypted at rest with AES-256. On premises you supply the encryption key and the certificate. Tokens and credentials are kept encrypted in secret management tools.

Only authorized Curiosity personnel can access production systems, and only when required. Internal roles follow least privilege and need to know.

Each customer’s data is kept in an isolated tenant. An on premises deployment is your own environment.

Cloud deployments are hosted with providers certified to standards such as ISO 27001 and SOC 2. The Security and Compliance Overview sets out the full posture. Download it from the resources page.

Yes. Curiosity is a German company and GDPR compliant, and a DPA is available. The Data Protection and Processor Policy is available on request.

It is set out in the Incident Response and Breach Policy. Request it from the resources page.

Single sign on works with Google, Microsoft, Okta, Auth0 and SAML2, with MFA enforced in your identity provider. Access is relationship based, for teams, workspaces and user roles, and synced from your source systems. Ask us about provisioning for your directory.

Yes. User actions, downloads, exports and AI interactions can be logged. Admins can restrict features per user, and models, data sources and tools per workspace.

Yes. Studio runs as a container on your servers or in your private cloud, and on Windows. Your data stays in your environment, and with an offline license the deployment can run fully air gapped.

On premises, one: Mixpanel, for product usage analytics. Cloud deployments use five. Both lists are on the subprocessors page. The authoritative register is a document, available on request.

Yes. Use a bundled local model, a hosted provider, an OpenAI compatible endpoint, or vectors you compute yourself. A different model means a new embedding index, and the graph is not touched.

Connectors write each record's access as team and user restrictions, and Studio checks them on every query, down to node types and fields. A revoked access applies on the next query after the connector syncs it, with no reindex.

Yes. Curiosity.Library gives you the graph and its queries from C# or Python, and you publish your own REST endpoints in C# inside Studio. Studio also serves an MCP server and an OpenAI compatible chat API.

No. It is a typed property graph stored in RocksDB, with nodes and their edges kept in memory for traversal, and full text and vector indexes in the same process. There is no RDF or SPARQL layer.

No. Studio keeps a synced copy of the records it needs and links back to each source. Your systems keep their role, their validation and their audit trail.

Deployments run over 30TB of connected data in production.

Yes. Add pattern spotters, spotters learned from nodes already in the graph, and trained entity models. In C# you can post-process each entity type, or write a code index that runs on every change to a node type.

Only when you ask for one. Tokenizing, entity spotting and linking run locally without a model. From code, StructuredAI classifies and scores text with a local model by default, or with an LLM provider you name.

When your connector syncs the change, the node is updated in place by its key and queued for every index, so parsing, embeddings and entity links catch up without a full rebuild.

Studio ships Harrier, Arctic XS and MiniLM, which run in process with no network. You can also call OpenAI, Azure OpenAI, Anthropic, Cohere, Google or any OpenAI compatible endpoint, or store vectors you compute yourself.

Yes. From code you can query the vector index directly, by text or by vector. In search, vector hits are added to keyword results or rerank them, each above a similarity cutoff you set, so exact part numbers still match.

A model is fixed per embedding index, so you create a new index with the new model and it embeds the field from the start. The graph, its nodes and your code are not touched.

Not through the built in tools: they search and read as the user who asked. Your own tool code gets both an unrestricted query and one scoped to the current user. Use the scoped one, and limit who may call a tool with its access groups.

Every agent run is stored as a record: the prompts, each tool call with its arguments, its result and how long it took, and the calls of any agent it handed work to. A wrong answer is a thing you can read rather than guess at.

They can call tools you register, including ones that write. What those tools permit is your decision.

No. Without a license key Studio runs with every feature on, for up to ten test users, with no time limit for development use.

No, and on purpose. The UI talks to its own session API. Your code uses the Library API with a token you can revoke, or the REST endpoints you write in C# inside Studio.

Yes. Studio commits every configuration change to a git repository and can push it to your remote. Schemas, endpoints, AI tools, agents and tasks are files you can review, and you import them back as a bundle or from the command line.

C#, for endpoints, AI tools, scheduled tasks, code indexes and connectors, with the same types Studio uses. Connectors can also be written in Python.

Extensions are kept as source and compiled by Studio, so an upgrade compiles them against the new version and a break shows as a compile error, not a silent failure. Stay on the documented surface (Graph, ChatAI, AgentAI) and it holds.

Yes. Push your own front end, written in C#, to Studio over git. It compiles each commit to a preview, and you promote the one you want to live.

Every result is checked against the user's teams and restrictions when the query runs, down to node types and fields. What those restrictions are depends on what your connector syncs from the source.

Wherever you deploy. Search, embeddings, entity extraction and OCR run inside Studio, and with a local model nothing goes to an AI provider. Set MSK_DISABLE_TELEMETRY and MSK_DISABLE_CLOUD_ERROR_REPORT to stop usage counts and error reports going to Curiosity. The front end reports product usage to Mixpanel.

Yes. Admins choose which actions are logged, then filter and download the trail. The log files carry a hash chain you can verify from the command line, which also converts them to CSV or JSON for your own retention.