Keep Agility PIM as the system that models your B2B catalog and publishes it to web, EDI and print. Add Anglera to complete those records from supplier spec sheets, with a citation on every value, written back through Agility's API.
Agility PIM and Anglera solve different halves of the problem — this page is about the seam between them.
Agility PIM and Anglera work on the same record from opposite ends: Agility decides how a product is modeled, approved and published, and Anglera is the standing practice that goes to the supplier's documents and brings back the value each attribute is waiting for.
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 Agility PIM leaves on your desk.
Ingests supplier files and feeds; PDF spec mining not documented
PDFs, spec tables, drawings, manuals, images, sites
Data model set in workshops; team adds attributes
Proposes fields your schema never had
Business rules and data quality routines; team defines values
Normalizes and governs allowed values, versioned
Unlimited parallel taxonomies; auto-classification not documented
Auto-classifies; channel and marketplace mapping
Auditable supplier loads; per-value source citation not documented
Every value cites its source doc and page
Versioned content per customer segment and locale
B2B specifier and B2C shopper enriched differently
Not documented; team brings search and review findings
Reviews, search, competitor rails, social — fed back
AI generates names, descriptions and SEO-oriented content
Original copy per persona and channel
Manages images, video and documents; generation not documented
Generates studio-grade imagery for photoless SKUs
Rule-based workflow triggers; team drives re-enrichment
Re-enriches on its own after go-live
Completeness analytics; publishing gated on data-complete rules
Scored against your standards; nothing publishes below bar
Publishes to web, marketplaces, EDI and InDesign print
Writes back to PIM, ERP, warehouse, commerce
RESTful API with full read/write; MCP not documented
API, webhooks, and MCP servers
Software platform; your team owns 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.
"Bought 40 of the 6-inch wafer downlights for a remodel. About half flicker at low end on the dimmers already in the wall. Had to swap dimmers on a second trip."
The record carries lumens, wattage and selectable CCT, but nothing about how the driver dims or which controls were tested. That lives in the manufacturer's dimmer compatibility chart, so the contractor learns it on site and the return reads as a defect.
dimming_method, plus minimum_dim_level_percent and a reference to the tested-dimmer listForward-phase (TRIAC / incandescent) | Reverse-phase (ELV) | 0-10V | Non-dimmable; minimum dim level as an integer percent; taken from the manufacturer's compatibility chart, not the cut sheet headline.Queries like "r290 reach in 2 door" and "hydrocarbon prep table 48" return the whole refrigeration category, because refrigerant appears only inside the spec sheet PDF.
Refrigerant type is not a structured attribute, so there is nothing to facet on and nothing to send to a channel that asks for it. Operators replacing equipment for a specific refrigerant scroll every reach-in by hand.
refrigerant_type, plus refrigerant_charge_ozASHRAE designations: R-290 | R-600a | R-134a | R-404A | R-448A | R-449A; charge as a number in ounces; system of record is the unit data plate and the manufacturer spec sheet.A run of cut-resistant work gloves bounces from a contractor's procurement catalog that requires a cut rating. The record says "high cut protection"; the manufacturer's certification sheet says ANSI A4.
Cut protection exists as marketing prose instead of a rated value, so the customer's required field has nothing to receive and the items stay off the buyer's approved list until someone reads certification sheets.
ansi_cut_level, plus en388_cut_ratingANSI/ISEA 105 cut levels A1 to A9; EN 388 cut letter A to F; values from the glove's certification sheet, not the catalog description.Agility's analytics let a team spot missing attributes and incomplete ranges in real time, and its workflow triggers can hold a product back until the data is complete. That is real discipline. But complete means complete against the data model and taxonomies agreed in the implementation workshops. A year later a manufacturer switches a cooler line to a new refrigerant, a contractor customer's procurement catalog starts requiring a glove cut rating, and electricians keep asking which dimmers a downlight works with. None of those questions has a field, so every record still passes the gate. A distributor's catalog drifts next to a well-run PIM not because the data is wrong, but because the model stopped moving while suppliers and buyers kept going. Keeping it current is weekly work: propose the field, fill it from the spec sheet with a citation, push it back into Agility.
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 Agility PIM stops.
How Schema Foundry works
Agility PIM, from insightsoftware (formerly Agility Multichannel), is a single-tenant cloud PIM for manufacturers, distributors and retailers. It models complex B2B catalogs with parallel taxonomies and inherited attributes, onboards supplier data through a governed integration module, and publishes one master record to web, marketplaces, EDI feeds and print through an in-house Adobe InDesign connector.
Pricing: Annual subscription per instance. Its UK G-Cloud 14 listing shows £48,000 to £100,000 an instance a year, with no free trial; other pricing is by quote.
Agility PIM websiteDistributors, wholesalers and manufacturers with deep B2B catalogs, many locales and a live print catalog program, who want parallel taxonomies, role-based workflows, governed supplier onboarding and an in-house InDesign connector in one PIM.
We'd rather tell you here than in month three of an implementation.
Capability verdicts reviewed against Agility PIM's public documentation on October 16, 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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