Curiosity

Integrations

Integrations connect Curiosity Studio to external systems for ingestion, synchronization, and workflow automation.

Common categories:

  • Data source integrations: import content from storage, databases, and SaaS systems
  • API integrations: pull or push data via REST APIs
  • Event-driven integrations: react to changes (webhooks, queues)
  • Downstream integrations: send signals/actions to other systems (tickets, notifications)

Choosing the right integration approach

  • Use a connector when you need full control over mapping and graph relationships.
  • Use a configured integration when the source system is standard and configuration is sufficient.
  • Use scheduled tasks when data changes periodically and near-real-time sync is not required.

See Data Integration → Connectors.

For a one-off CSV file, Data → Import Data maps the columns to the fields of a new or existing node type, with no connector to write:

The Import data from a file dialog with support-technicians.csv loaded: the target node type name, each column mapped to a field with TechnicianId as the key, and a preview of the rows.The Import data from a file dialog with support-technicians.csv loaded: the target node type name, each column mapped to a field with TechnicianId as the key, and a preview of the rows.

Integration design principles

  • Idempotent writes: repeated runs should not create duplicates.
  • Stable identity: consistent keys for nodes and edges.
  • Incremental updates: sync deltas where possible.
  • Observability: log counts, failures, and latency.
  • Security: store credentials in a secret manager; minimize token scopes.

Common patterns

  • Ingest → index → enrich

    • ingest structured records
    • index key fields for search
    • apply NLP/embeddings where beneficial

  • Retrieve → decide → act

    • retrieve candidates (graph + search)
    • decide using business rules and/or LLM assistance
    • act through an endpoint that writes back or calls external APIs

Next steps