What it sells
In-store analytics AI assistant to fix your retail stores
Business model breakdown
Buyer: who owns the budget?
UnverifiedRetail ops, store innovation and multichannel heads at store-based retailers (testimonial titles: Head of Multichannel Operations Development, Store Innovation Lead).
Trigger: what makes them buy now?
UnverifiedNeed accurate footfall, conversion and staffing data per store without buying overhead sensors; wanting to know if store decisions worked in hours not quarters.
Workflow: what inputs become what output?
Plug a small APU into the store internet and camera network; AI on existing cameras counts footfall, queues, dwell, heatmaps, demographics and separates staff from customers; managers query results in plain language via Ask Aura.
Economics: what it saves and how it charges
Software subscription with a small on-site device; claims staff/customer segmentation raised conversion-report accuracy by 24% (Purple).
Distribution: how it reaches customers
Demo-led ("Book a call"), trade shows (NRF Europe), case studies with A.S. Watson Kruidvat, DFS, Onitsuka Tiger, Virgin Media O2, Adidas Dubai, Flannels; white-label Spatial Insights partnership with Telefonica Business (2024).
Funding history and coverage
| Round date | Stage | Amount | Investors | Source |
|---|---|---|---|---|
| — | Y Combinator Winter 2019 | — | Y Combinator | ycombinator.com |
Profiles summarize public reporting and company websites. Business-model notes are MaxBC's reading of that material, not confirmed facts; unknowns are left blank rather than guessed. Updated 2026-10-12.