Store-level 3D shelf digital twins built from retailer planogram files

Store-level 3D shelf digital twins built from retailer planogram files. Customers upload JDA/PSA planograms (v8-v10+), product master files and store lists; the platform builds an exact spatial model of each shelf — X/Y/Z capping, orientation and volume-fill 'to 100% accuracy to the PSA file' — then computes facings, share of shelf, adjacency and compliance metrics, revenue-velocity heatmaps, and derived analytics such as the 'Halo Effect' between adjacent SKUs, 'visual suffocation' where high-potential items are blocked by low-value bulk, dormant versus high-velocity shelf zones, under-spaced SKUs relative to sales velocity, and prioritised field fix lists with version-tracked execution history. Also holds store metadata and demographics used for assortment insight

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Brickroad customers

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Coverage

Universe, instruments and categories.

Industry: Application SoftwareFood Retail
Instruments: equities
Categories: Alternative

Dataset card

Type: not stated
Format: Multimodal: structured tabular planogram and product-master records (CSV/XLSX/ZIP and native PSA files) transformed into 3D spatial models, plus exportable reports and a REST API; SOC 2 compliant and Azure-hosted with regional data residency
Volume: Not published. Bounded from the product: volume scales with stores x bays under management, and a single retailer tenant can span thousands of stores with tens of bays each — so one mid-size chain yields hundreds of thousands of 3D bay models per planogram version. The platform supports multi-planogram comparison within a store (e.g. 24ft versus 4ft layouts) and version-tracked history, which multiplies stored models per bay
Users: N/A in consumer terms — tiered B2B SaaS (Starter, Professional, Enterprise subscriptions) sold to category managers, merchandising-ops leads and BI analysts; client and seat counts are unpublished
History: 3 years
Update frequency: not stated
Growth: Active — the vendor states continuous weekly feature updates, and the product surface includes recently shipped capabilities (AI data mapping at 97%+ field-detection accuracy, schema-drift warnings, what-if scenarios, supplier-shared dashboards) plus SOC 2 attestation and regional data residency, indicating ongoing enterprise hardening
Launched: est. 2023-2025 — the property presents as a current-generation product (Azure-native, SOC 2, AI-driven mapping, LLM-era feature set) with no funding record, press footprint or archive trail located; the company describes itself as built by retail operations engineers, i.e. founded by practitioners rather than spun out of an existing vendor
Delivery: not stated
Entity mapping: not stated
Sample: not stated
Point-in-time: not stated
Licence: not stated

supplier index read from their site