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Agentic Product Data Enrichment

Make products easier to find, compare, and buy by completing the catalog details that search engines and AI assistants need.

Turns fragmented supplier documents and manufacturer sites into complete, source-backed product records.

What the agents do

Retrieves missing facts from supplier PDFs, manuals, and manufacturer sites on its own, normalizes them to catalog rules, and cites a source for every value.

Built by
Anglera, a Coveo company, which builds and runs the enrichment agents
Contributed by
Coveo (Owns Anglera and runs the enrichment agents in production)
Industry
Apparel & Footwear, Retail, Manufacturing & Industrial, Grocery, Automotive, Healthcare
Audience
B2B, B2C
01
The problem

Why this exists

Search engines and AI assistants can only recommend products they can understand. In many catalogs the details buyers rely on are missing, inconsistent, or buried in supplier PDFs, manuals, and manufacturer websites: dimensions, materials, pressure ratings, compatibility, and every other attribute that decides a purchase.

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New SKUs and supplier updates outpace the teams doing manual enrichment, so product discovery stays a constant effort and further investment in the buyer experience waits. The catalogs that hurt most are B2B and B2C ones where a single product carries hundreds of technical attributes and accuracy is not optional.

02
Outcomes

What changes when this is in place

  • Enriched product pages drew 120% more organic landing-page traffic than control pages in a 30-day A/B test.
  • AI-referred visits to the enriched product pages rose 270% over the control group in the same test.
  • About 300 SKU variants at an apparel retailer received enriched attributes during that test.
03
How it works

Architecture

For each product in scope, a set of agents retrieves the missing facts from the places they already live: supplier documents, spec sheets, technical manuals, product images, and manufacturer websites. It then normalizes what it finds to the customer's catalog rules, converting values and units, mapping facts to the taxonomy, and applying attribute definitions across the products in scope.

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Every value keeps its source citation and a confidence score. Conflicting or uncertain values are flagged for a person to review, against acceptance criteria and authoritative sources the customer defines. New SKUs and supplier changes run through the same rules, so enrichment keeps running as the catalog changes.

Enriched records return to the customer's product information or enterprise resource system, or to the commerce platform, through files, interfaces, or scheduled transfers, where they are stored and published as usual. The richer data also reaches the pages and feeds that external assistants and shopping agents read, which supports answer engine and generative engine optimization.

Anglera's enrichment agents retrieve missing facts for each product from supplier documents, spec sheets, technical manuals, product images and manufacturer websites. They normalize the facts to the customer's catalog rules, covering units, taxonomy and attribute definitions, and every value keeps a source citation and a confidence score. Conflicting or uncertain values go to a person, who reviews them against the customer's acceptance criteria and sources. Enriched records return to the PIM, ERP or commerce platform through files, APIs or scheduled transfers, and reach the product pages and feeds that search engines, AI assistants and shopping agents read. New SKUs and supplier changes run through the same rules.

Anglera's enrichment agents retrieve missing facts for each product from supplier documents, spec sheets, technical manuals, product images and manufacturer websites. They normalize the facts to the customer's catalog rules, covering units, taxonomy and attribute definitions, and every value keeps a source citation and a confidence score. Conflicting or uncertain values go to a person, who reviews them against the customer's acceptance criteria and sources. Enriched records return to the PIM, ERP or commerce platform through files, APIs or scheduled transfers, and reach the product pages and feeds that search engines, AI assistants and shopping agents read. New SKUs and supplier changes run through the same rules.
Tech stack
PIMERPREST APIsScheduled file transfers
Next step

Request an intro

Coveo is behind this solution. Ask about enriching your product catalog with source-backed attributes, and the MACH Alliance will put you in touch with the person who can answer.

The MACH Alliance passes your details to a named contact at Coveo who knows this work and can answer your questions. We aim to reply within 2 business days. Your details are handled under the MACH Alliance privacy policy.

Not ready to talk to anyone? MACH Insider is the Alliance mailing list. New solutions, program openings, and the research behind them, once a month.

Everyone credited on this solution

  • CoveoOwns Anglera and runs the enrichment agents in production

Every organization named here has a page listing the rest of its work on the Hub.

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Related solutions

Verification

Contributor submission

The detail on this page comes from the contributor's own account of their own work. The MACH Alliance reviews a submission before publishing it and does not independently verify the figures in it.

What this page does not establish

  • The apparel retailer that ran the A/B test is not named.
  • The test measured traffic, not conversion or revenue, so no commercial lift is established.
  • The size and composition of Anglera's customer base are not disclosed.
  • How the Coveo Commerce add-on is priced or licensed is not established.

Where this came from

Drawn from Coveo's submission to the Agent Solutions Hub, October 2026.

Status: Live in productionAdded Oct 30, 2026A listing is an editorial decision, not a MACH Alliance certification.

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