Live

Retail AI: Catalog & Product Intelligence

Turning chaotic supplier feeds into a coherent product graph that humans and agents can reason over.

SKU stability

99.2%

ID resolution

Defect rate

-41%

Post-normalization

Latency

120ms

p95 read path

Sources

180+

Integrated feeds

The Problem

Hyperscale catalogs ingest millions of updates daily from overlapping sources. Without strong identity resolution and normalization, personalization and agentic retrieval amplify errors instead of value.

The AI Architecture

Entity resolution, attribute harmonization, taxonomy services, and enrichment pipelines with human-in-the-loop for edge cases. Downstream features consume stable IDs and versioned attributes rather than raw strings.

The ROI/Outcome

Improved coverage and consistency unlock safer agent answers and faster merchant tooling. Metrics focus on defect rate, time-to-publish, and downstream retrieval precision—not vanity accuracy.

Tech Stack

Ingestion

  • Streaming ETL
  • Schema contracts
  • Quarantine queues

Graph

  • Entity resolution
  • Hierarchy services
  • Search indexes

Quality

  • Validators
  • Sampling
  • Owner workflows

AI

  • Embeddings
  • NER assists
  • RAG grounding