Store Intelligence

Computer vision that detects out-of-stocks, verifies planograms, and routes dollar-ranked tasks to your store teams before the sale is lost.

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They miss phantom inventory, planogram violations, and out-of-stocks in low-traffic sections. Manual audits sample a fraction of shelves. Image recognition finds 50-200% more gaps than traditional scanning methods. The gaps you are not finding today are the ones costing you the most.

Every shelf scanned, every gap scored

Computer vision detects out-of-stocks, planogram violations, misplaced items, and pricing errors across your entire store network. No manual audits. No sampling.

Tasks ranked by dollars at risk

Every issue is ranked by revenue impact and aligned with active promotions and available inventory. Your teams fix the highest-value problems first.

Phantom inventory caught early

When the system says “in stock” but the shelf is empty, replenishment never triggers. Store Intelligence finds what conventional inventory systems cannot see.

Shelf data your CPG partners will pay for

Turn store execution data into a revenue stream. CPG brands get real-time availability, share of shelf, and compliance reporting through structured collaboration programs.

Raw, siloed data

Data lakes, legacy systems, cloud DBs

Ingest and clean

Agents normalize and prepare

Contextualize with ontology

Agents map entities and relationships

AI-ready data

Clean, contextualized, and governed

Store Intelligence is adding AI assistants that go beyond detection, diagnosing root causes and recommending actions.

StoreAI Assistant (coming soon)

Continuous monitoring across all store execution dimensions. Detects patterns across OSA, compliance, and labor allocation; surfaces prioritized recommendations for store operations leaders.

Unified Shelf Assistant (coming soon)

Connects assortment optimization, space planning, and computer vision to close the gap between planned shelf strategy and actual store-level execution.

+9 points
on-shelf availability at a major U.S. convenience retailer
91% reduction
in shelf scanning labor: 5.5 minutes to 30 seconds per section
+21 points
planogram accuracy at a leading Canadian grocer. Sustained over 12 weeks, with +2% category sales
+4%
revenue increase at a 1,000+ location U.S. convenience chain after full rollout
+7 points
on-shelf availability and +20 points planogram execution, deployed at scale across the entire network
2-5%
sales increase across Store Intelligence deployments
+6 points
Average OSA improvement (Europe +3.9 points, U.S. +8.5 points)
+18.9 points
Average shelf compliance improvement (Europe +15.9 points, U.S. +22.0 points)
What is the difference between AI shelf monitoring and manual shelf audits?

Manual audits cover a fraction of products on a sample basis. Computer vision scans every product position. Retailers using image recognition typically find 50-200% more gaps than traditional methods.

How does computer vision detect phantom inventory?

Phantom inventory means the system shows “in stock” but the shelf is empty, so replenishment never triggers. Computer vision sees the actual shelf, compares it to system records, and flags the mismatch. One customer found 15% of out-of-stocks were phantom.

Can CPG partners access shelf intelligence data?

Yes. Retailers share shelf-level execution data with CPG partners through structured collaboration programs. CPGs gain real-time visibility into in-store execution. Retailers generate incremental revenue.

What image capture options are available?

Mobile capture (smartphones), ISG camera systems, and third-party robotic platforms. No store WiFi or fixed infrastructure required for mobile capture.