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Documentation Index

Fetch the complete documentation index at: https://docs.getclaro.ai/llms.txt

Use this file to discover all available pages before exploring further.

A Catalogue is a typed object — Products, Suppliers, Line Items, Variants, etc. — that holds your records and everything that acts on them. Catalogues are persistent: they accumulate history, track provenance per field, and survive across operations and runs. Multiple catalogues can exist in a workspace and can reference each other (e.g. Product.supplier → Supplier).

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The five tabs

Each catalogue opens with five tabs along the top.

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Attributes

The schema for the catalogue. Each attribute is a typed field:
  • text — free text or constrained patterns
  • number — integers, decimals, with optional units
  • image — single image or gallery, with metadata (dimensions, format)
  • date — date or datetime, with timezone handling
  • enum — a fixed value set, with optional ordering
  • reference — a pointer to a record in another catalogue
Per-attribute settings include: required, default value, validation rules (regex, range, length), and (for references) the related catalogue and reverse relationship name. Edit the schema at any time — Claro tracks attribute history alongside record history. Adding or changing an attribute does not destroy existing data; type migrations produce a preview before they are applied.

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Records

The actual rows. Sortable, filterable, editable in a spreadsheet-like grid.
  • Inline edits create change events with provenance.
  • Per-field history is browsable and roll-back is per-field.
  • Filters, saved views, and bulk edits are first-class.
  • Each record has a stable identity that survives across data source updates.

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Data Source

The upstream feeds that populate the catalogue.
  • File upload — CSV, XLSX (one-off or repeated)
  • Scheduled scrape — URL templates with mapping
  • HTTPS pull — periodic pulls of JSON or CSV endpoints
  • Supplier Portal — submissions land here pre-mapped
  • Database connectors — BigQuery, Postgres, Supabase
  • Email-as-source — emails to a workspace address are parsed
Each source has its own mapping to the catalogue’s attributes, its own schedule, and its own conflict policy (overwrite, append, write-if-empty).

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Operation

The transformations available against this catalogue. The Operations tab is the launch surface for Export, Price Insights & Monitoring, Bulk Enrichment, Analyse, Data Source Mapping, Push & Sync, Enrich Images, SEO Report, Find Duplicates, Find Similarities, Validate Data, Normalize Data, and Generate Taxonomy. Operations can be run on demand, scheduled, or chained. Every run produces a reversible diff and confidence per change. See Operations for the full reference.

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Config

Governance for the catalogue.
  • Access — who can read, edit, and approve.
  • Retention — history depth, archival rules.
  • Write-back targets — which downstream connectors are allowed.
  • Default reviewers — who receives review queue items.
  • Auto-apply thresholds — per-operation and per-attribute confidence cutoffs.

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Relationships between catalogues

Reference attributes connect catalogues. A Product.supplier reference to a Supplier catalogue carries:
  • Forward navigation from product to supplier on the Records grid.
  • Reverse navigation from supplier to all related products.
  • Cascade rules on supplier merge or delete.
  • Cross-catalogue filtering (e.g. all products from suppliers in Germany).
Operations can read across references — Bulk Enrichment can use values from a referenced supplier record as context, for example.

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History and provenance

Every value in the Catalogue carries the source of its last write — which operation, which run, which underlying data source, which model, which reviewer. This is visible inline on every cell and is the basis for:
  • Roll-back — per-field, to any prior value.
  • Audit — full activity trail per record.
  • Trust — every model-generated value is traceable to its inputs.

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Promoting a dataset to a Catalogue

Datasets produced by Research Agents are not catalogues by default. To promote one:
  1. Open the dataset in Generated Datasets.
  2. Choose Promote to Catalogue.
  3. Pick the target catalogue type or create a new one.
  4. Map columns to attributes; new attributes can be created on the fly.
Once promoted, the records become persistent and subject to all the same operations, provenance tracking, and review gates as native catalogues.