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Akeneo
Connect your AI to Akeneo
Product data managers, merchandisers, and digital asset managers keep every product, family, attribute, and asset in Akeneo, but spotting weak records, structural gaps, or stale data means scrolling grids and opening list after list. AI can surface those answers in seconds, but only if it respects Akeneo's channel, locale, and category scoping and never treats draft or disabled products as published, so access stays read-only.
Why it matters
Capabilities that matter most for Akeneo
01
Read-only catalog access
Popdock exposes Akeneo products, product models, families, attributes, categories, and channels as read-only data, so AI answers from the catalog without any risk of changing it.
02
Assets and workflows included
Asset families, assets, workflows, and workflow tasks are available alongside products, so one question can cover content, media, and enrichment backlog.
03
Ready-made app store tools
Every list ships as a Get data tool in the app store, so teams start with 19 working tools instead of building queries.
03
Cross-system answers
Pair Akeneo with Business Central, Dynamics GP, Sage Intacct, or NetSuite to compare catalog products with ERP items, stock, and prices by SKU.
05
Governed AI
Answers respect Akeneo channel, locale, and category scoping, and disabled products are never presented as published.
Use cases
Example AI Use Cases for Akeneo
scenario
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Attribute definitions in Akeneo drift over time. Attributes end up in no group or a group that no longer exists, groups sit empty, and flags such as unique and value per locale get combined in ways that cannot work. Nobody sees these problems until an import fails or a channel export breaks.
What popdock provides
--
Optionally name an attribute type, and PopdockAI reads the attributes and attribute groups in Akeneo and checks them against the catalog modeling rules: attributes with a missing or unknown group, groups with no attributes, unique attributes that are also set per locale or per channel, and attributes with no labels. Each finding gives the attribute code, the rule it breaks and a suggested fix, with a count per rule at the end. It only reads, nothing in Akeneo is changed, and it reports only what Akeneo returns.
Business outcome
---
Modeling mistakes in your attribute setup surface in one report, with a suggested fix for each, before they break an import or an export.
scenario
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Select attributes in Akeneo collect options over the years. Some have no label, some differ from another only by case or punctuation, and some share a sort order. These quietly corrupt filters and exports, and finding them means opening the option list one attribute at a time.
What popdock provides
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Give an attribute code and PopdockAI first confirms the attribute exists in Akeneo and is a select type, and stops if it is not. It then reads every option and flags those with no label, codes that differ only by case or punctuation, and repeated sort order values. You get the option count and a suggested clean-up list. It only reads, so no option is changed or removed.
Business outcome
---
You get a clean-up list of duplicate and unlabelled options for one attribute, so filters stay reliable and nothing is edited by accident.
scenario
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Product managers scroll the Akeneo product grid looking for weak records, and the ones that matter get missed. Products with a poor data quality rating and gaps in name, brand or categories can go live, and nobody can easily rank which ones to fix first.
What popdock provides
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Name a product family and an optional maximum rating, and PopdockAI reads the low-rated products in that family from Akeneo, defaulting to a rating of 2 or lower. It checks each one for empty names, brands, colors, short descriptions and categories, and ranks enabled products first, then by the number of gaps. It ends with the three most common gaps. It shows the enabled flag on every row and never treats a disabled product as live. It only reads, and it does not claim to check custom attribute values it cannot see.
Business outcome
---
You get a ranked fix list for the weakest products in a family, with live products first and nothing in Akeneo changed.
scenario
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Before promoting a product, someone checks the Akeneo record for content and category, then opens Dynamics GP for the item, its price list and stock by site. It takes two screens and a few minutes per SKU, and gaps such as no price entry or zero stock are easy to miss.
What popdock provides
--
Give a SKU and optionally a Dynamics GP company, and PopdockAI reads the product from Akeneo and the matching item from Dynamics GP, including price levels and quantities by site. It shows one block per system and ends with a verdict of ready or blocked, listing every reason, such as a disabled product, missing categories, no price entry, zero stock or a discontinued item. If a system lacks the SKU it says so and stops cleanly. Stock is shown per site and never added together without saying so. It only reads.
Business outcome
---
One answer shows whether a SKU is ready to sell, with every blocking reason listed, instead of two screens and a guess.
scenario
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Before a launch, someone opens Akeneo and Business Central side by side to confirm a product is enabled, priced and in stock. The two systems each hold part of the answer, and a mismatch such as an enabled product with a blocked item is easy to miss by eye.
What popdock provides
--
Give a product identifier and optionally a Business Central company, and PopdockAI reads the product from Akeneo and the item with the same number from Business Central. It checks enabled against blocked, a unit price above zero, inventory above zero, quantity on purchase order when inventory is zero, and whether the descriptions roughly agree. You get a verdict of Ready, Needs attention or Not in ERP with a table of each check. It stops if there is no match or more than one, shows both values when the systems disagree and never decides which is right. It only reads.
Business outcome
---
A launch check that took two systems and some guesswork becomes one verdict with every check shown, and no record is changed.
scenario
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Before publishing or promoting a product, someone checks the Akeneo record and then logs in to Sage Intacct to see whether the item is active and stocked. The second look often gets skipped, and a product goes live that has no free stock.
What popdock provides
--
Give a SKU and optionally an Intacct company, and PopdockAI reads the product from Akeneo, then the matching Sage Intacct item and its stock in each warehouse. It stops if nothing matches or if several products match. You get a header line, a warehouse table and a verdict: ready, enabled but no free stock, or disabled but stocked, with the numbers behind it. If an item has no warehouse rows it says there is no recorded stock rather than zero. It only reads on both systems.
Business outcome
---
You know whether a product has free stock before it is published, with the numbers shown and nothing changed in either system.
scenario
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Someone looks up a product in Akeneo, then searches NetSuite separately for its stock by location and bin. The two views drift apart, and an enabled product with no available stock, or a disabled one still holding stock, can go unnoticed.
What popdock provides
--
Give a SKU and PopdockAI reads the product from Akeneo, then the matching NetSuite item and its stock by location and bin. It stops if no single product or item matches. You get a line with the product name, family and enabled status, then a table of quantity on hand and available with totals. It flags an enabled product with no available stock and a disabled one that still holds stock. If an item has no stock records it says so rather than reporting zero, and shows both numbers when the item total and the location rows differ. It only reads.
Business outcome
---
Stock by location sits next to catalog status in one answer, so mismatches show up without a second search.
scenario
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Product names are keyed twice, once in Akeneo and once as an item description in Dynamics GP. Over time the wording drifts, so listings and reports describe the same SKU differently and nobody knows how many disagree.
What popdock provides
--
Name a brand and optionally a Dynamics GP company, and PopdockAI reads up to 40 Akeneo products for that brand and looks up each SKU as a GP item. It lists each SKU with both names and a verdict of same, differs in case or spacing only, or differs in wording. It ignores case and repeated spaces, treats a description that is a shortened form of the name as truncated, and reports SKUs with no GP item or no Akeneo name separately. It does not say which system is right. It only reads.
Business outcome
---
You see exactly which SKUs have drifted names between Akeneo and Dynamics GP, with cosmetic differences separated from real ones.
scenario
-
Sales teams copy a SKU between Akeneo and NetSuite to see price levels, and products with no price slip through before they are published. Akeneo holds the catalog status and NetSuite holds the prices, so every check is a manual lookup in two places.
What popdock provides
--
Give a SKU and optionally a price level, and PopdockAI reads the product from Akeneo, confirms the item exists in NetSuite, then reads its prices. You get a table of price level, minimum quantity, price and currency with the lowest price first, plus the Akeneo enabled status. It flags an enabled product with no price rows and any price of zero, shows both descriptions when they differ, and never adds or compares prices across currencies. Prices always come from NetSuite, never from Akeneo. It only reads.
Business outcome
---
You see every NetSuite price for a product next to its catalog status, so unpriced products are caught before they are published.
scenario
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Cross-sell, upsell and related product links in Akeneo live in a separate list from the product, so reading them means looking up each target by hand. It is hard to see what a product is linked to, and whether those links point at products that are even enabled.
What popdock provides
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Give a product identifier and PopdockAI finds the product in Akeneo, stopping and listing the matches if there is none or several. It reads the product's associations and the association types, noting which are two-way or quantified, and groups the links by type with the kind and identifier of each target. For product targets it looks up up to 20 and shows each name and whether it is enabled. It says so when there are no associations. It only reads, so no link is added or removed.
Business outcome
---
A product's cross-sell and related links appear as one grouped answer with target names and status, and no link is edited.
scenario
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Customers see products as available in the catalog that the ERP has blocked or run out of, and nobody notices until a complaint. Finding them means checking each enabled Akeneo product against its Business Central item one at a time.
What popdock provides
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Optionally name a brand and an inventory threshold, and PopdockAI reads up to 100 enabled products from Akeneo, then looks up each as a Business Central item. It reports two tables, blocked items and items at or below the threshold with inventory, quantity on purchase order and vendor, ordered by brand, then lists products that have no item. If the list is capped it says the result may be incomplete, and it flags products where a lookup returns several items. It only reads, and follow-up actions are suggested in words only.
Business outcome
---
Enabled products that cannot be sold are listed in one report, so the catalog can be corrected before customers notice.
scenario
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Catalog teams keep promoting products that the ERP shows have no stock or have not sold in months, because the Akeneo list and the Sage Intacct item data are never put side by side. Dead stock stays on the front page while better sellers get less attention.
What popdock provides
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Optionally name a family, a number of days (180 by default) and an Intacct company, and PopdockAI reads up to 50 enabled products from Akeneo and looks up each one's Sage Intacct item. It flags products whose last sale is older than the cutoff or empty, and those with no stock on hand, as no recent sales, no stock or both. You get counts, then a table oldest first, then products with no item. It only suggests candidates and never recommends disabling a product. It only reads on both systems.
Business outcome
---
Marketing sees which enabled products are not moving, ranked and with the numbers shown, so promotion goes to products that sell.
scenario
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Enabled products keep showing in the catalog after Dynamics GP has run out of stock or never received a price, so customers order what cannot ship. Finding them means looking up each product's stock and price list in GP by hand.
What popdock provides
--
Name a product family and optionally a company, and PopdockAI reads up to 40 enabled products from Akeneo, then checks each SKU's quantity on hand across sites in Dynamics GP and on order. For items with no stock it also checks whether any price list entry has a price above zero. You get a table with total on hand, on order and priced yes or no, with no stock and nothing on order first, plus counts. A SKU with no GP record is reported as not in the ERP, not as zero stock. It only reads.
Business outcome
---
Enabled products that cannot be fulfilled are listed with their stock and price status, so catalog and supply teams can act on them.
scenario
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Enabled products stay live in the catalog after stock runs out because nobody cross-checks NetSuite, so customers see items that cannot ship. The check means looking up stock for each Akeneo product in a second system.
What popdock provides
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Optionally name a family and a record limit, and PopdockAI reads enabled products from Akeneo, 50 by default, and adds up the available quantity in NetSuite for each. Products with no rows are looked up as items to see whether they exist at all. It reports three groups: zero or negative available stock, no NetSuite item, and products with stock as a count only, with counts first. A missing stock record is labelled as no stock record, not proof of no stock, and a sample is called a sample. It only reads.
Business outcome
---
Enabled products with no available stock are grouped by reason, so you fix the catalog or the ERP record rather than guess.
scenario
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Nobody notices Akeneo products that have not been touched in months, so outdated data lingers in the catalog. The product grid can filter by date, but building the cutoff and summarising by family is manual work that rarely gets done.
What popdock provides
--
Optionally give a number of days, 180 by default, and a family, and PopdockAI works out the cutoff date, states it, and reads the products in Akeneo that have not been updated since. You get a table of identifier, name, family, brand, enabled, updated and created, oldest first, with counts by family and the share that are enabled. If the result is capped it says the list is partial and suggests narrowing by family. If nothing is older than the cutoff it says so. It only reads.
Business outcome
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Out of date products are listed oldest first with the cutoff stated, so cleanup can start where the data is most neglected.
scenario
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Procurement and merchandising keep brand lists and vendor lists apart, so nobody knows which Akeneo brands have a payable vendor in Sage Intacct or what is owed to them. Matching the two means searching vendor names by hand, one brand at a time.
What popdock provides
--
Optionally name a country and an Intacct company, and PopdockAI reads up to 50 brands from Akeneo and looks each one up as a Sage Intacct vendor by name, first exactly and then by name contains. It marks exact and contains matches separately and shows vendor id, status, terms and amount owed. You get counts, a table, brands with no vendor, and brands that matched several vendors with their candidates, where it never picks one. A name match is a candidate, not proof of the same company, and inactive vendors are flagged. It only reads.
Business outcome
---
Finance and procurement see which brands have a vendor and what is owed, with uncertain matches left for a person to decide.
scenario
-
Merchandisers judge an Akeneo product family by catalog data alone, because sales numbers live in Dynamics GP and are tedious to match back by SKU. Which products in a family actually sell, and which have not sold at all, takes a spreadsheet to find out.
What popdock provides
--
Name a family, an optional start date (90 days ago by default) and a Dynamics GP company, and PopdockAI reads up to 40 products in that family from Akeneo and adds up each SKU's sales order lines in Dynamics GP since the start date: units, revenue, documents and customers. You get a table ranked by revenue and a separate list of products with no sales, with the period stated. It warns that the totals mix document types and are not netted for returns, and that amounts in different currencies are not added. It only reads.
Business outcome
---
A family's products are ranked by what they actually sold in Dynamics GP, with the period stated and no sales listed apart.
scenario
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Merchandisers and ERP teams compare the Akeneo catalog with the Dynamics GP item list in spreadsheets. Products go live with no item to sell or stock, and GP items sit with no catalog record, and neither side is noticed until an order or a listing fails.
What popdock provides
--
Optionally name a family and a Dynamics GP company, and PopdockAI reads up to 50 enabled products from Akeneo and looks up each SKU as a GP item, then samples 50 GP items and checks each against Akeneo. You get counts and three lists: matched SKUs with item class, in Akeneo only, and in Dynamics GP only, clearly labelled as a sample. A SKU that matches only after trimming or case changes is listed as a format mismatch, not a match. A missing record is a finding, not an error. It only reads on both systems.
Business outcome
---
You see which catalog products have no GP item and which GP items have no catalog product, without a spreadsheet and without changing a record.
scenario
-
Merchandisers compare the Akeneo export with the Sage Intacct item list in spreadsheets, so products go live with no item to sell or stock. Items that Intacct has made inactive can also stay on the catalog because the two lists are never lined up.
What popdock provides
--
Optionally name a family and an Intacct company, and PopdockAI reads up to 50 enabled products from Akeneo and looks up each SKU as an Intacct item, then samples 50 Intacct items and checks each against Akeneo. You get counts and four lists: matched and active, matched but inactive in Intacct, in Akeneo only, and in Intacct only, labelled as a sample. A SKU that matches only loosely is reported as a format mismatch, not a match. A missing record is a finding, not an error. It only reads on both systems.
Business outcome
---
Missing and inactive items are listed against the catalog in one report, so products are not published without something to sell.
scenario
-
Catalog and ERP teams compare Akeneo exports with NetSuite item lists by hand, and products or items that exist on only one side go unnoticed. The comparison is repeated every time the catalog changes, and the results are out of date almost at once.
What popdock provides
--
Optionally name a family and a record limit, and PopdockAI reads enabled products from Akeneo, 50 by default, and looks up each SKU as a NetSuite item, then samples the same number of NetSuite items and checks each against Akeneo. You get counts and three lists: matched SKUs, in Akeneo only and in NetSuite only, with the NetSuite side clearly labelled as a sample. If a lookup returns several records it lists them and does not pick one, and a loose SKU match is a format mismatch. It only reads on both systems.
Business outcome
---
You see which enabled products have no NetSuite item and which sampled items have no catalog product, in one reconciliation.
scenario
-
Product data managers compare the Akeneo catalog with the Business Central item list by hand in spreadsheets. SKUs that never made it into the ERP are found only when an order fails, and near matches are easy to mistake for real ones.
What popdock provides
--
Optionally name a brand, a maximum number of products (50 by default) and a Business Central company, and PopdockAI reads enabled products from Akeneo and looks up each SKU as a Business Central item by exact match. If there is no exact match it tries once by description and marks any hit as a possible match, not a confirmed one. You get three lists, confirmed, possible match only and no item, with blocked, unit price and inventory for matches, plus counts. Ambiguous matches are flagged, and it stops on an error rather than reporting partial results. It only reads on both systems.
Business outcome
---
Catalog products with no ERP item are found before an order fails, with uncertain matches kept clearly apart from confirmed ones.
scenario
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Akeneo asset families grow without review. Nobody checks how the media attributes are set up or which assets were uploaded or changed recently, so gaps in naming and required media are found only when a product page looks wrong.
What popdock provides
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Name an asset family and an optional start date (the last 30 days by default), and PopdockAI reads the family settings and its attributes from Akeneo, noting the main media attribute, naming convention and attributes required for completeness. It then reads the assets changed since the start date. You get the family settings, the attributes by media type, the number of recent assets and the newest ten asset codes with created and updated dates. If the family is not found it lists the available codes. It only reads.
Business outcome
---
An asset family's setup and recent changes are summarised in one answer, so media gaps are caught before they reach a product page.
scenario
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Brand reference data in Akeneo is checked by eye against the brands used on products. Brands that no product uses stay in the reference list, and mismatches between the two go unnoticed until a filter or a listing looks wrong.
What popdock provides
--
Optionally name a tier, and PopdockAI reads the brand reference records from Akeneo. For each brand code, up to 15, it counts the products that use that brand. You get a table of brand code, label, tier, country and product count, with brands that have no products flagged. It only reads, so no brand record or product is changed.
Business outcome
---
Brands with no products are flagged in one table with product counts, so brand data stays aligned with the catalog.
scenario
-
Akeneo channels point at category trees that nobody reviews. A channel with a missing root, no locales or an empty tree means products silently fall out of a storefront, and the cause is only found after the fact.
What popdock provides
--
Optionally name a channel, and PopdockAI reads the channel from Akeneo, or every channel if none is given, with its category tree, locales and currencies. It then reads the categories under each channel's tree root and counts them. You get one block per channel with the tree root, the number of categories, locales and currencies, and any problem found, such as a missing root, no locales, no currencies or a tree with no children. If the channel is not found it lists the available codes. It only reads.
Business outcome
---
Channel and category tree gaps are found in one pass, so products do not silently drop out of a storefront.
scenario
-
Variant structure errors in Akeneo are hard to spot across parent and child records. A product model with no children, or one with no categories, hides inside a family, and checking means opening each model and counting its variants by hand.
What popdock provides
--
Name a family and PopdockAI reads its family variants and product models from Akeneo, then counts the child products for each model, checking up to 25. You get a table of model code, family variant, parent model, child count and categories, with models that have no children or no categories flagged, and the family variants with their variant attribute sets. If there are more than 25 models it says it sampled the first 25, and if the family has no variants it reports that and stops. It only reads.
Business outcome
---
Product models with no variants or categories are flagged for a family in one table, so structure errors are found without opening each model.
scenario
-
Akeneo workflow tasks pile up, and the overdue or rejected ones are found by chance. Seeing the backlog by workflow and step means opening each workflow in turn and reading its tasks one by one.
What popdock provides
--
Optionally name a workflow, and PopdockAI reads the workflows and their steps from Akeneo, then the tasks for each. It treats tasks with a due date before today as overdue and tasks marked rejected as rejected. You get counts per workflow and step, then a table of the overdue and rejected tasks with the product or product model, step, status and due date. If no workflow matches it lists the available ones. It only reads, and it never changes a task status.
Business outcome
---
The workflow backlog is counted by workflow and step, with overdue and rejected tasks listed, and no task is changed.
scenario
-
Support cases about a product sit in NetSuite while the product content sits in Akeneo, so recurring complaints never reach the catalog owners. Linking a case to a product record means finding the NetSuite item first, then searching cases by its internal id.
What popdock provides
--
Give a SKU and PopdockAI reads the product from Akeneo, finds the matching NetSuite item and reads the support cases raised against it, stopping cleanly if the product or item is missing. You get the product name and short description, a table of case number, date, type and title newest first, and a short list of recurring themes. It then suggests which catalog fields to review. It says so when there are no cases, does not infer a cause the case text does not state, and changes nothing in either system.
Business outcome
---
Recurring support issues are tied back to catalog fields worth reviewing, so product content improves from what customers actually ask about.
scenario
-
Buyers look up a catalog product in Akeneo, then hunt through Dynamics GP vendor items and vendor records to see who supplies it. Lead times, last receipt cost and whether the vendor is on hold are spread across several screens.
What popdock provides
--
Give a SKU and optionally a Dynamics GP company, and PopdockAI reads the product from Akeneo and its vendor items from Dynamics GP, then each vendor's record. You get the product line first, then one row per vendor with status and hold, vendor item number, lead time, minimum order, last receipt date and cost, and quantity on order. It flags vendors that are on hold or inactive and vendor ids that point at no record, and notes if the brand matches a vendor name without assuming they are the same company. Costs are not converted. It only reads.
Business outcome
---
Buyers see who supplies a product, with lead times, cost and vendor status together, in one answer.
scenario
-
Managers cannot see what changed in the Akeneo catalog this week without opening every list. New and edited products, product models and assets are spread across screens, so a simple question about catalog activity takes a manual search.
What popdock provides
--
Optionally give a start date, 7 days ago by default, and PopdockAI reads the products, product models and assets in Akeneo that changed since then, and separately the products created since then, so new records are told from edits. You get counts of new and updated records for each type, the top families and brands touched, how many products are enabled versus disabled, and ten example records. If any list hit the record limit it says the counts are lower bounds. It only reads.
Business outcome
---
Leaders get a short summary of what changed in the catalog over a period, with new records told apart from edits.
scenario
-
Planners hop between Akeneo and the Sage Intacct sales and purchasing screens to see how much of one product has been sold and bought lately. Totals have to be added up by hand, and the top customers and vendors are hard to see.
What popdock provides
--
Give a SKU, an optional start date (the last 90 days by default) and an Intacct company, and PopdockAI reads the product from Akeneo, then its sales order lines and its purchasing lines in Sage Intacct since the start date. You get the product header, sales totals with the top five customers by amount, and purchasing totals with the vendors used. It says plainly when there is no sales or no purchasing activity, states that the order lines mix document types, and reports a product with no ERP lines as having no recorded demand. It only reads.
Business outcome
---
Sales and purchasing for one product are totalled in one answer, with the top customers and vendors named.
scenario
-
Planners hop between Akeneo and the NetSuite order screens to see what is on order and what has sold for one product. The sales and purchase order lines are in separate lists, and statuses and quantities have to be read by hand.
What popdock provides
--
Give a SKU and an optional date, and PopdockAI reads the product from Akeneo, confirms the item in NetSuite, then reads its sales order lines and its purchase order lines. When a date is given it drops purchase lines dated before it. You get the product name, enabled flag and on-hand quantity, then a sales order table and a purchase order table with line counts and the total purchase quantity. Statuses are shown exactly as returned, and it states that sales lines here carry no quantity, so demand is a line count. It only reads.
Business outcome
---
Demand and supply for one product appear in a single answer, with statuses shown exactly as NetSuite returns them.
scenario
-
To answer whether a product can be sold, someone checks Akeneo, then the Business Central item card, the vendor list and the open purchase and sales orders, in separate screens. The net position is worked out by hand, and the headline numbers do not always agree with the lines.
What popdock provides
--
Give a product identifier and a look-back period for sales lines (90 days by default), and PopdockAI confirms the product in Akeneo, then reads its Business Central item, its vendors and its open purchase and sales order lines. You get the product summary, inventory, committed sales quantity, incoming purchase quantity and the net position, then the vendor list and the soonest expected receipt. It stops if the product or item is missing, shows both numbers when line totals disagree with the item quantities, and says none found rather than inferring zero demand from an empty list. It only reads.
Business outcome
---
Net supply and demand for a product is worked out in one answer, with vendors and the next receipt, and disagreements shown rather than hidden.
No items found.
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