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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.

Operations are the building blocks of the Catalog Operations workflow. Every operation runs against a catalogue (or a filtered subset), produces a reversible change set, and writes scored, traceable updates back to records. This page is the reference for every operation currently available. Find them under the Operation tab on any catalogue.

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How operations run

An operation always:
  1. Reads records (the entire catalogue, or a saved filter).
  2. Optionally calls models, web sources, or another catalogue.
  3. Produces a run — a record of inputs, outputs, and per-change confidence.
  4. Writes back changes, gated by the auto-apply / review / reject thresholds you’ve configured.
Operations can be:
  • Run on demand — single execution against a filter.
  • Scheduled — recurring (hourly, daily, weekly, on-event).
  • Chained — output of one operation triggers the next (e.g. Onboard → Validate → Normalize → Bulk Enrich → Push & Sync).
Every run is reversible. The catalogue maintains per-field history; rolling back affects only the field(s) you select.

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Operation reference

OperationWhat it does
ExportProduce a file in CSV, XLS, Shopify, or Amazon format. Filters and column selection are honored.
Price Insights & MonitoringConfigure recurring price checks across marketplaces; pricing trends and anomalies feed into Monitor → Price.
Bulk EnrichmentFill missing or incomplete attributes at scale. Sources can be web search, model generation, supplier lookup, or another catalogue.
AnalyseRun the data-quality report (per-field scores, distribution stats, critical issues, overall score).
Data Source MappingMatch uploaded files to existing records using text similarity scoring; produces a mapping draft you can review before merge.
Push & SyncPush records to Shopify or Amazon (Beta). Maps catalogue attributes to platform fields per a configurable schema.
Enrich ImagesGenerate or repair images with metadata: alt text, primary subject tags, dimensions, format normalization (Beta).
SEO ReportScore listings on SEO health and produce optimization suggestions per field (Beta).
Find DuplicatesIdentify duplicate records using AI matching; produces merge proposals you can approve in bulk (Beta).
Find SimilaritiesGroup similar records into clusters and surface relationships; useful for variant grouping and supplier match (Beta).
Validate DataRun schema, format, and rule checks; produce an issue list with severity (Beta).
Normalize DataStandardize formats — units, currencies, dates, casing, language — across selected fields (Beta).
Generate TaxonomyPropose a hierarchical taxonomy from your records. Output goes to the Taxonomy surface for curation and versioning (Beta).

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Export

Produce a file in CSV, XLS, Shopify-ready, or Amazon-ready format.
  • Inputs — catalogue or filter, column selection, output format.
  • Outputs — a downloadable file, with a record of the export in run history.
  • Formats — generic CSV/XLS, plus marketplace-shaped templates that match required columns and value formats for direct upload.

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Price Insights & Monitoring

Configure recurring price checks across marketplaces. Detected drifts and anomalies feed into Monitor → Price.
  • Inputs — catalogue, target SKUs, source marketplaces, cadence, alert rules.
  • Outputs — price history time series, drift alerts, pricing dashboards.

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Bulk Enrichment

Fill missing or incomplete attributes at scale. The most-used operation in most workflows.
  • Inputs — catalogue or filter, target attribute(s), source (web search, model generation, supplier lookup, another catalogue, Knowledge Base), prompt and grounding, confidence thresholds.
  • Outputs — proposed values per record with confidence and citations. Auto-applied above threshold; queued in Notifications below.
  • Tips — start narrow (one attribute, 100 records), tune the prompt and threshold, then expand.

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Analyse

The data-quality report described in Modules → Analyse.
  • Inputs — catalogue or filter.
  • Outputs — per-field scores, distribution stats, critical issues with one-click follow-on operations, overall Data Quality Score.
  • Side effects — none. Analyse never modifies records.

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Data Source Mapping

Match the rows in an uploaded file (or any new Data Source) to existing records using text similarity scoring before merging.
  • Inputs — Data Source, target catalogue, fields to drive matching, threshold.
  • Outputs — a mapping draft: matched, unmatched, ambiguous. Review before merging.
  • Use — first stage of every onboarding pipeline; keeps duplicates out of the catalogue.

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Push & Sync (Beta)

Push records to Shopify or Amazon. Maps catalogue attributes to platform fields per a configurable schema.
  • Inputs — catalogue or filter, target connector, mapping, conflict policy.
  • Outputs — a run with success/failure counts and per-record errors. Errors include the platform-side response.

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Enrich Images (Beta)

Generate or repair images with metadata.
  • Inputs — catalogue or filter, image attribute, target metadata (alt text, subject tags, dimensions, format).
  • Outputs — alt text, structured tags, normalized image variants, with confidence per generated value.

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SEO Report (Beta)

Score listings on SEO health and produce per-field optimization suggestions.
  • Inputs — catalogue or filter, target attributes (title, description, meta, alt text), keyword sources.
  • Outputs — per-record SEO score, per-field recommendations, opportunity list.

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Find Duplicates (Beta)

Identify duplicate records using AI matching; produce merge proposals.
  • Inputs — catalogue, fields to weight, similarity threshold.
  • Outputs — clusters of likely duplicates with per-pair confidence; merge proposals you can approve in bulk via Similarity & Duplicate.

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Find Similarities (Beta)

Group similar records into clusters; useful for variant grouping and supplier match.
  • Inputs — catalogue, fields to weight, threshold.
  • Outputs — clusters with intra-cluster similarity scores and visualizations.

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Validate Data (Beta)

Run schema, format, and rule checks against records.
  • Inputs — catalogue or filter, ruleset (built-in plus custom rules).
  • Outputs — an issue list with severity, attribute, and a suggested fix where applicable.

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Normalize Data (Beta)

Standardize formats — units, currencies, dates, casing, language — across selected fields.
  • Inputs — catalogue or filter, target fields, normalization rules (currency target, unit system, date format, casing).
  • Outputs — proposed normalized values with provenance back to the original.

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Generate Taxonomy (Beta)

Propose a hierarchical taxonomy from your records. Output goes to the Taxonomy surface for curation and versioning.
  • Inputs — catalogue, fields used for clustering, target depth, optional seed taxonomy.
  • Outputs — a draft taxonomy with proposed assignments per record. Curate, then publish a version.

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Confidence, review, and rollback

Three settings govern how aggressive each operation is:
SettingEffect
Auto-apply thresholdConfidence above which a write happens without review.
Review thresholdBelow auto-apply but above this — queues for review.
Reject thresholdBelow this — discarded with a logged reason.
Defaults are conservative. Per-operation, per-attribute, and per-source overrides are supported. Every write is reversible. The catalogue maintains a per-field history; rolling back affects only the field(s) you select, and a roll-back is itself a logged event. See Confidence Scoring for how the score is computed.

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Chained pipelines

Operations can be chained — the completion of one triggers the next. A typical onboarding pipeline: 
Data Source Mapping
        ↓
Validate Data
        ↓
Normalize Data
        ↓
Bulk Enrichment
        ↓
Push & Sync
Each stage gates the next, so failures and below-threshold items in any stage halt the pipeline (or branch to review) before the catalogue is touched.