AI Native IR for
Modern Trade Execution
SCAI Vision analyses shelves, aisles and promotional displays to identify availability gaps, measure share of shelf, verify planogram and POSM compliance, detect competitor presence and surface the next action for merchandisers and key account teams.
AI-Native Image Recognition
AI Native IR
Built for Modern Trade
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Why Traditional Modern Trade Audits
Fail to Improve Execution
Six Retail Execution Checks from Every Shelf Photo
Every shelf image is analyzed in seconds to deliver AI-powered insights for availability, shelf share, compliance, competition and fraud detection.
Availability / OOS
Detect stock-outs instantly and improve on-shelf availability.
Share of Shelf
Measure your brand's shelf presence vs. competitors. Track facings, position, & dominance.
Planogram Compliance
Verify planogram compliance and detect execution gaps instantly.
Competitor Detection
Monitor rival SKU activity, new product launches, & pricing moves across outlets.
Fraud Detection
Detect fake photos, duplicate submissions and GPS fraud automatically.
POSM Compliance
Verify display materials, branding assets, and promotional setups are in place & compliant.
Compare Every Shelf with
the Approved Planogram
SCAI Vision compares each shelf scan with the approved planogram and scores facings, position and adjacency done simply by stitching overlapping shots into one. Key account managers and merchandisers can see which store or fixture has moved away from the approved layout without waiting for the next scheduled audit.
Measure Share of Shelf and Competitor Presence
SCAI Vision measures facings, linear shelf space and eye-level position by stock-keeping unit and brand. It also captures the competitor products shown in the image so teams can compare share-of-shelf results across stores and retail formats.
Measure Multiple Shelf-Execution KPIs From One Scan
One shelf scan can provide availability, share-of-shelf, branding-visibility and new-launch distribution checks without separate manual audit steps.
Detect empty shelves before sales are lost
Most audits report OOS after the fact. SCAI Vision trends availability by store, category, and day-part, so gaps surface while there’s still time to restock before the next customer walks the aisle.
Built for the Precision of Modern Trade
SCAI Vision connects shelf images with store-level compliance, competitor comparison and account-team reporting rather than presenting only a single audit score.
SKU Availability and Assortment Compliance
Each scan is compared with the approved assortment for that store. Missing stock-keeping units are shown as availability gaps for the current visit.
Price-Tag and Pricing Compliance
SCAI Vision reads shelf-edge labels, promotional tags and maximum retail price stickers alongside the product to identify missing, mismatched or outdated pricing.
Promotion and Secondary-Display Execution
End caps, gondolas, island displays and other promotional units can be checked alongside the primary shelf to record campaign execution.
Questions about SCAI Vision for Modern Trade
A merchandiser photographs the shelf, and one scan returns six checks at once:
The model trains on your SKUs in 3 clicks, scores in under 3 seconds, and runs at 3x lower cost than conventional IR.
"Native" means the recognition output doesn't stop at measurement. Because SCAI Vision runs on the same composable micro-services platform and the same data spine as SFA, DMS, and eB2B, a detected shelf gap becomes a display task on the merchandiser's app during the same visit, and execution scores feed the same KPI engine leadership already reviews.
Standalone IR tells you what the shelf looked like; AI Native IR changes what happens to the shelf before the visit ends.
From that single photograph, the scan returns:
The visit then continues rather than ending. Gaps become corrective tasks in the app, the merchandiser fixes what can be fixed and re-scans for before-and-after verification, and the store closes with a verified execution record rather than an audit finding. That's the practical difference between an IR tool and IR inside the execution system.
The system:
Distinguishing near-identical packs is a model-training question, not a feature question — which is why the 3-click training matters here too. Your specific competitive set can be trained into the model for your categories and markets, rather than relying on a generic global catalogue that has never seen the packs on your shelf.
This is the highest-value use of IR in modern trade. Display and visibility spend is contracted and paid in advance, so an unexecuted end cap is money already spent for nothing — and the only way to recover or renegotiate it is documented, store-level, dated proof. IR converts trade-spend verification from a sampling exercise into a census.
Pricing is modular, so IR is added to your existing platform rather than bought as a separate system with its own integration cost.
The saving is structural, not a discount: conventional IR is expensive mostly because of what it takes to make it work at all. Exact pricing depends on scope, SKUs, and store count — so get a custom demo and a quote for your assortment.
Show Us a Better IR for Modern Trade. Win 1 Million $
Get a Big 4 firm to audit your platform against ours. Score higher on capability. We cut the cheque.
Open to any competing AI Native IR MT provider. Provider must be ready for an audit by a Big 4 firm using a scorecard agreed with SalesCode.ai.
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