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  • Get startedProduct availability and preview limitationsUnderstand what works in the frontend and which product capabilities are not connected yet.
  • Get startedBuild your first RAG pipelineBuild and inspect your first seven-node Basic RAG graph and learn what validation means.
  • Build pipelinesBasic RAG and Hybrid Search templatesCompare Ragify's two starting graphs and decide which pattern to explore.
  • Node referenceUnderstand the node libraryBrowse the ten registered node types by role in the workflow.

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Concept and roadmap

Planned chatbot integration flow

See how a deployed Ragify pipeline could connect to an external chatbot once backend services exist.

The long-term integration model separates the pipeline builder from the application that asks questions. A developer uses Ragify to define the knowledge-retrieval workflow, then integrates its deployed query endpoint into an external chatbot or web application.

Conceptual sequence #

  • Design a pipeline with appropriate loading, processing, retrieval, and output stages.
  • Validate graph structure and configuration.
  • Persist the pipeline and its authorized metadata on a backend.
  • Ingest source documents and prepare any necessary vector or keyword indexes.
  • Deploy the pipeline execution service.
  • Create a scoped API credential or other supported authentication method.
  • Send an authenticated query request from the external application's server.
  • Receive a response or structured failure, then display it responsibly to the end user.

Frontend versus backend #

Once a pipeline endpoint is truly deployed, an external chatbot would communicate with the backend endpoint rather than with Ragify's visual editor. The editor remains the place for configuring and managing the pipeline. This is an architecture goal, not a current deployment feature.

Safe integration principle #

Keep private keys on a trusted backend, rate-limit and authorize requests, define reasonable timeouts, and avoid leaking sensitive inputs in logs. These safeguards must be implemented, tested, and documented before production use.