Torra Docs

Platform Architecture

The runtime model behind Torra's knowledge-grounded and multimodal execution.

Runtime position

Torra is the answer and execution layer that sits on top of model providers, knowledge infrastructure, and business workflows.

Core system flow

  1. Files land in raw storage and are normalized into document pages, slides, and clean text.
  2. Normalized chunks are embedded and stored with collection and source metadata.
  3. Retrieval pulls candidate chunks and reranks them before answer assembly.
  4. Torra formats the answer, preserves citations, and reuses the evidence package for downstream generation.

Why this matters

  • The retrieval layer stays replaceable.
  • The answer format stays product-defined.
  • The same evidence package can support ask, doc, deck, and media generation flows.
  • Teams can review outputs against cited source material instead of trusting an opaque model response.

Architecture principles

  • Lead with ownership of the knowledge layer.
  • Keep citations visible and reviewable.
  • Treat answer formatting as a product responsibility.
  • Reuse one governed runtime across every team rather than splitting by model or modality.

Typical operators in the stack

  • Torra ingestion for normalization
  • Vector index and metadata store for retrieval
  • Reranking for evidence quality
  • Torra answer layer for formatting, citation, and workflow reuse

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