Buy Outfindo if you want a guided-selling widget that walks shoppers to the right SKU. Buy Anglera if you need cited, normalized data written back into your PIM so search, marketplace, EDI and ERP all use it.
Both claim to enrich product data. This page is about where that claim stops.
Outfindo is built to make discovery work — a guided-selling layer that asks shoppers questions instead of showing dropdown filters, with enrichment gathering the attributes those questions need — while Anglera starts at the other end, on the operational job of completing SKUs against a schema across a supplier base and keeping them complete as manufacturers restate specs and categories add drivers.
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 Outfindo leaves on your desk.
Diver mines manufacturer sites, reviews, databases, product images
PDFs, spec tables, drawings, manuals, images, sites
Beacon derives parameters from consumer research; suggests attributes
Proposes fields your schema never had
Normalizes units, standardizes values; no versioned pick lists documented
Normalizes and governs allowed values, versioned
Classifies product type; suggests category tree for ACP
Auto-classifies; channel and marketplace mapping
Every claim traced to source; no source, no claim
Every value cites its source doc and page
Beacon quantifies buyer segments, matches their language; B2C-oriented
B2B specifier and B2C shopper enriched differently
Forums, reviews, guides feed Diver's enrichment; no search queries
Reviews, search, competitor rails, social — fed back
Translates specs to customer language; full PDP copy unclear
Original copy per persona and channel
Reads attributes from images; does not generate images
Generates studio-grade imagery for photoless SKUs
Claims real-time pulling; autonomous re-enrichment not documented
Re-enriches on its own after go-live
Flags missing parameters; no catalog health scoring found
Scored against your standards; nothing publishes below bar
Feed or API delivery to PIM/warehouse; connectors undocumented
Writes back to PIM, ERP, warehouse, commerce
API confirmed; no documented webhooks or MCP server
API, webhooks, and MCP servers
Positions as fully automated pipeline; software, not people
Anglera owns the work; review is a guardrail
“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.
"Runs 700x45c fine until you bolt the guards on — then the rear tyre kisses the seatstay bridge at anything over 42c."
The catalogue carries one tyre clearance number, taken from the frame spec sheet. Real clearance is two numbers, and the one that drives returns is the guarded figure nobody publishes.
max_tyre_clearance_guarded_mm (paired with max_tyre_clearance_unguarded_mm)Integer millimetres, measured at the narrowest point (chainstay bridge, seatstay bridge, or guard stay — whichever is tightest). Guarded value populated only where mudguard_mounts = present; where it is not published, it stays unavailable rather than inheriting the unguarded number.Repeated zero-result queries: "e-mount weather sealed under 600g", "sealed lens rain", "dust resistant 24-70"
Sealing lives in marketing copy — "dust and moisture resistant" on one line, "designed for outdoor use" on the next. There is no field to filter on, so the query returns nothing and the shopper leaves for a forum thread.
environmental_sealing_levelGoverned set: none | gasket_mount_only | full_body_sealed | ip_rated. ip_rated requires a stated IP code from the manufacturer; brochure phrases like "weather resistant" map to gasket_mount_only only when the manufacturer names the sealed points, otherwise unavailable.Their listing shows "SEER 8.5 / SCOP 4.6 (average climate), A+++ / A++"; yours shows "A+++" and a single kW figure.
Efficiency is a per-mode, per-climate-zone reading, and heating performance in a cold zone is often the number that decides the purchase. Collapsed to one energy label, the SKU reads as interchangeable with a unit that heats far worse in January.
scop_by_climate_zone / seer_coolingSCOP recorded as a decimal per zone from the governed set: average | warmer | colder, each sourced from the EU energy label. energy_class held separately per mode (cooling_class, heating_class_by_zone) rather than as one blended grade.Outfindo states the standard plainly on its product data page: every claim traceable to a specific source — manufacturer data, expert reviews, or verified databases — and missing data marked unavailable rather than invented. Anglera's argument is that the standard only holds if it is re-applied. A clearance figure lifted from a 2023 expert review is a different asset from the same figure on the current datasheet, and the difference surfaces the day a supplier restates it. So govern three things per value, not per SKU: which source it came from, when it was last confirmed against that source, and which governed set it belongs to. Then `unavailable` stays a legitimate state with a reason attached, the PIM keeps storing the record, and the completion work runs alongside it on a schedule.
Values are normalized into a governed, versioned set of allowed values — so a filter works, and keeps working after the next import.
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.
Filling the fields you defined has an invisible ceiling: a catalog can hit 100% complete and still miss the attribute that loses the sale, because completeness is measured against a schema someone drew years ago. Schema Foundry reads competitor listings, buyer searches, review complaints and your supplier docs, and proposes the fields you never defined — which is where Outfindo stops.
How Schema Foundry works
Outfindo is an AI-powered guided selling and product data enrichment platform for ecommerce retailers. Its core product is an embeddable product-selection widget ("Product Guide") that walks shoppers through a question flow to recommend the right SKU; it uses proprietary AI agents (Beacon and Diver) to source and enrich product data in support of that front-end experience.
Pricing: Not publicly listed; custom pricing behind a sales conversation.
Outfindo websiteB2C retailers whose gap is shopper conversion, not catalog operations. Beacon and Diver research consumer language and buying criteria, then feed the question flow that closes the sale.
We'd rather tell you here than in month three of an implementation.
Capability verdicts reviewed against Outfindo'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 and your supplier files. In 30 minutes you'll see it enriched — complete, structured, and consistent enough to launch on — plus the attributes your schema didn't have yet.
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