Buy Catalog if you are a consumer brand whose problem is getting found in ChatGPT and Gemini; buy Anglera if your problem is the depth and correctness of the catalog itself, inside a system of record you already own.
Both claim to enrich product data. This page is about where that claim stops.
Every tool in this market sells you one act and calls it the whole play. The useful question isn't whether Catalog is good at its act — it's what happens to the other two.
Mine every spec from every source.
Every value traced to a document you can open. The catalog is only as honest as what it was built from.
Aim the catalog at the buyer who actually buys.
Grounded data still loses if it answers questions nobody asked. Alignment is what turns specs into conversion.
Product data is a practice, not a project.
Markets move, suppliers reissue, buyers change what they ask for. A catalog that is right in March is wrong by August unless something is watching.
Scored against public documentation. Grouped by the three acts — so you can see which ones Catalog leaves on your desk.
Mines web pages, images, reviews; no supplier PDFs
PDFs, spec tables, drawings, manuals, images, sites
Enriches into fixed 86-field schema; no field discovery
Proposes fields your schema never had
Normalizes specs and variants; no versioned pick lists
Normalizes and governs allowed values, versioned
Classifies products; maps to Google, ACP, UCP formats
Auto-classifies; channel and marketplace mapping
Per-field last_seen_at freshness; no source citations
Every value cites its source doc and page
Agent-optimized output; no B2B/B2C persona variants
B2B specifier and B2C shopper enriched differently
Reddit, Pinterest, Google reviews feed enrichment; query tracking
Reviews, search, competitor rails, social — fed back
Generates FAQs and use cases; structures existing copy
Original copy per persona and channel
Analyzes and serves image URLs; no image generation
Generates studio-grade imagery for photoless SKUs
Background re-enrichment; continuous price, stock, variant sync
Re-enriches on its own after go-live
AI readiness score, 90+ checks, competitor benchmarking
Scored against your standards; nothing publishes below bar
Publishes parallel AI storefront; no write-back endpoints
Writes back to PIM, ERP, warehouse, commerce
Public REST API; UCP/MCP distribution; no webhooks documented
API, webhooks, and MCP servers
Automated pipeline; brand reviews enrichments before publish
Anglera owns the work; review is a guardrail
Every enrichment tool on the market takes your schema as a given and fills the blanks in it. That ceiling is invisible: your catalog can hit 100% complete and still be missing the attribute that loses the sale — because completeness is measured against a schema someone drew years ago.
3/4 in0.75"3/4"19mm3/4 inchDN200.75 in (DN20)Six suppliers, six spellings, one physical size. Filters only work once they agree.
BlkblackBLACK MATTEMatte BlkRAL 9005Black — MatteFree text makes a colour filter useless. A governed value makes it a facet.
SS316316 StainlessStainless Steel 316A4 StainlessStainless Steel — 316 / A4Same alloy, four vocabularies, plus a trade name. Buyers search all of them.
“Buyer signals” is the emptiest phrase in this category, so here is the literal thing. Each of these is an observation from a live market, the gap it exposes, and the field that gets created as a result.
“Handle hits the wall when you open it” shows up across the 2- and 3-star reviews on a brass ball valve — and in the return reasons behind it.
Clearance is why the product came back, and no field anywhere describes it.
Handle Clearance (fully open)Millimetres, measured from valve centreline“left hand thread” is searched steadily on your own site and returns zero results — while you stock 240 left-hand-threaded SKUs.
You have the products. You do not have the attribute, so search cannot find them.
Thread DirectionRight-hand (RH) · Left-hand (LH)Contractors comparing compressors argue about noise in decibels months before any RFQ mentions it.
The dB rating is sitting in the supplier PDF. It is not a field, so it is not a filter.
Sound Level (dB)dB(A) at 1 m, integerFour of six competitors let a buyer filter welders by duty cycle. Your category has no such field.
Buyers who filter on duty cycle never see your catalog at all.
Duty Cycle% at rated amperage (e.g. 60% @ 200 A)Page 4 of the datasheet has “Ambient operating range −20 °C to +60 °C” in a table nobody ever mapped.
The data arrived years ago and died in a PDF because no field was waiting for it.
Ambient Operating RangeMin/max °C pairListings bounce for a missing Country of Origin that is printed on the packaging and in the customs paperwork.
A required field for the channel that was never required by the PIM.
Country of OriginISO 3166-1 alpha-2Catalog is a San Francisco startup (founded 2025, $3M pre-seed led by Acrew Capital with WndrCo and Hustle Fund) building product data infrastructure for agentic commerce. It ingests a brand's catalog from Shopify, WooCommerce, BigCommerce, Adobe Commerce and others — plus reviews and shopper signals from Reddit, Pinterest and Google — then normalizes and enriches products into 86+ machine-readable fields. It distributes that data to AI shopping surfaces (ChatGPT via ACP, Gemini via UCP, Claude, Perplexity, Amazon Rufus, Google Merchant Center) and publishes a parallel "AI storefront" on a brand subdomain. A separate developer API sells product extraction from any URL.
Pricing: Split. The developer API publishes per-call rates: Crawl $0.2/100 listings; Extract $2/100 (Starter), $10/100 (Scale, adds AI enrichment and Reddit insights), $100/100 (Pro, adds image/review analysis, FAQs, deep research). API keys issued by emailing the founders. The brand platform has no public pricing page (/pricing 404s); it is demo-booked, with a free AI readiness audit as entry.
Catalog websiteConsumer brands whose top priority is AI-channel visibility — ACP/UCP distribution, an agent-readable storefront, referral tracking — plus developers wanting per-call extraction from any URL.
We'd rather tell you here than in month three of an implementation.
Capability verdicts reviewed against Catalog's public documentation on July 14, 2026. Vendors ship quickly — if something here is out of date, tell us and we'll correct it.
Bring one category. We'll run Schema Foundry against it and show you the fields your schema doesn't have yet — on your own SKUs, in 30 minutes.
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