Keep Kontainer as your DAM and PIM — it stores assets, syncs to Shopify and ERP, and generates copy from fields you already have. Add Anglera to mine supplier docs for the specs those fields are missing.
Kontainer and Anglera solve different halves of the problem — this page is about the seam between them.
Kontainer gives a brand one governed place to hold its assets and its product records and to push both out to webshops, resellers and marketplaces; this comparison is about who establishes the values that go in those fields in the first place, because the record is a shelf and filling it is a practice, not a project.
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 Kontainer leaves on your desk.
Imports ERP/CSV/Excel feeds; no supplier document spec mining
PDFs, spec tables, drawings, manuals, images, sites
Customer defines all fields; no attribute discovery or proposals
Proposes fields your schema never had
Dropdown and resource lists exist; team curates allowed values
Normalizes and governs allowed values, versioned
Product Tree hierarchy and Smart Channels; classification done manually
Auto-classifies; channel and marketplace mapping
C2PA labels AI assets; no value-level source citations
Every value cites its source doc and page
Channel-specific text prompts; no B2B/B2C persona tailoring
B2B specifier and B2C shopper enriched differently
No review, search-query or competitor signals feeding enrichment
Reviews, search, competitor rails, social — fed back
AI descriptions and translations from PIM fields; custom prompts
Original copy per persona and channel
Background removal and AI tagging; no product image generation
Generates studio-grade imagery for photoless SKUs
User-triggered AI runs; syncs move data, don't re-enrich
Re-enriches on its own after go-live
Per-channel completeness widget; no health trending found
Scored against your standards; nothing publishes below bar
Pushes products and assets to Shopify, ERP, webshops
Writes back to PIM, ERP, warehouse, commerce
REST API, Swagger, OAuth, MCP integration; webhooks unconfirmed
API, webhooks, and MCP servers
Software platform; customer's team performs the enrichment work
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.
Three reviews on the same merino base layer say the size chart is "in the photo, not the text". One buyer gives a 96 cm chest, says they ordered L off the chart image, and reports the sleeve ran about 3 cm short of what the chart showed.
The size chart is governed as an asset and travels correctly with the image. The measurements inside it were never established as values, so nobody can filter on sleeve length, validate it against the pattern, or compare it across a season.
sleeve_length_cm (per size), chest_flat_cm (per size), fit_profilefit_profile: slim_fit | regular_fit | relaxed_fit | oversizedA marketplace bounces a batch of pendant lamps on "missing required: cable_length, light_source_included". Both values are on page 2 of the installation PDF attached to each record.
Distribution is configured and firing. Adding the two columns takes an afternoon; establishing the value for every lamp in the range, from a PDF nobody has read since launch, is the work that decides whether the feed clears.
cable_length_mm, light_source_included, ip_ratingip_rating: IP20 | IP23 | IP44 | IP54 | IP65 | IP67The competing page reads "FSC Mix, 70% certified content, oil-wax finish, two leaves, extends 180 to 260 cm". The equivalent own record has "Solid oak. Extendable." in the description and an ESG column that reads "Yes".
ESG data is centralised as a field, which is the point of centralising it, but the field is holding a claim rather than a value. "Yes" cannot be checked, compared, or defended to a buyer who asks which scheme.
certification_scheme, certified_content_pct, length_closed_mm, length_extended_mm, surface_finishcertification_scheme: FSC 100% | FSC Mix | FSC Recycled | PEFC | none_stated; surface_finish: oil_wax | hardwax_oil | lacquered | untreatedKontainer's PIM tracks completeness on a dashboard, runs validation rules and approval workflows, and flags corrupt data. That machinery answers one question well: is the field populated, and is the value the right shape? A cable length typed as 150 when the spec sheet says 1.5 m passes every rule it is asked. Kontainer also lists easy addition of new fields, so when a marketplace starts asking for recycled content, the column itself is a short job. The long job is the four thousand values that have to go underneath it — someone still has to read the spec sheet, open the installation PDF hanging off the record, and decide. And because Kontainer enriches DAM images with product data directly from PIM, a value nobody established doesn't sit still: it rides the asset out to resellers. Anglera works alongside the PIM and does that filling work.
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 Kontainer stops.
How Schema Foundry works
Kontainer is a Scandinavian-origin DAM and PIM platform that lets marketing and e-commerce teams store, organize, and distribute product data and digital assets (images, videos, PDFs, CAD files) from one system. It serves 350+ customers across fashion, architecture, manufacturing, and retail.
Pricing: Starts at ~$380/month (Business), $695/month (Professional), $1,155/month (Premium); Enterprise custom. 30-day free trial available.
Kontainer websiteMarketing and e-commerce teams who need one governed home for images, video, CAD and product data, with per-channel completeness checks and push to Shopify, ERP and webshops.
We'd rather tell you here than in month three of an implementation.
Capability verdicts reviewed against Kontainer'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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