Yaqaza · Pitch Deck
Hajj & Umrah · CROWD SAFETY OPERATIONS
Yaqazaيقظة
Computer vision that detects collapses, crowd-crush risk, and heat stroke — and dispatches before an operator sees the feed.
neuriya.ai — Sovereign, Arabic-first enterprise AI
Problem
Crowd emergencies are caught by operators watching screens, not by the system itself
- Collapse, crowd-crush density, and heat-related distress are currently caught only if an operator happens to be watching the right camera at the right moment.
- Manual dispatch after a phoned-in or radioed report can take minutes to reach the nearest team, in situations where seconds change the outcome.
- Existing CCTV estates across the Haram already capture the visual signatures of these events, but the footage is used for after-the-fact review, not real-time detection.
- After-action reviews of crowd incidents are reconstructed from scattered radio logs and camera timestamps, not one auditable record.
Solution
Existing CCTV becomes a continuous safety detector with automatic dispatch
Product
Yaqaza in action
How it works
From first touch to outcome
Watch continuously
Existing cameras are analyzed in real time for the visual patterns that precede or signal an emergency.
Detect and score
A candidate event is scored for confidence — collapse, crowd-crush density, or heat distress.
Auto-dispatch
Above threshold, the nearest team is dispatched automatically, with location and event type pre-filled.
Track to resolution
Operators follow the incident through the response queue until it is confirmed resolved.
Market
Sizing the opportunity
- TAM — $1.1B. MENA crowd-safety & CCTV analytics market
- SAM — $150M. Saudi Hajj-Umrah crowd-safety computer-vision detection market
- SOM — $11M. 3-year obtainable share via design-partner Haram operations and safety authorities
Peak Hajj and Umrah days concentrate millions of pilgrims into a few square kilometers, and crowd-safety incidents carry outsized consequences and scrutiny — making real-time detection on cameras Haram authorities already operate a direct fit for existing safety mandates.
Business model
How Yaqaza makes money
Per-camera / per-zone detection license
Subscription priced by the number of camera feeds or zones under active detection.
B2G / B2B via Haram operations authorities
Sold to crowd-safety and Haram operations authorities and large operators running their own safety teams.
Implementation & model-calibration fee
One-time fee to integrate camera feeds and calibrate detection thresholds to a specific site.
Revenue streams
Where the revenue actually comes from
Competition
Where we win
Our edge
- Runs on the CCTV estate the Haram already operates — no new camera procurement or hardware install cycle.
- On-premise, sovereign inference keeps footage in-Kingdom, satisfying PDPL and NDMO requirements global CV vendors can't match.
- Models are tuned specifically for collapse, crowd-crush density, and heat distress, not adapted from retail or perimeter-security use cases.
- Founding team combines Saudi crowd-operations experience with computer-vision engineering.
Traction
Early validation, built for pilot readiness
- Full detection and dispatch product experience designed and built end-to-end: detection log, response queue, incident detail, after-action record.
- Architecture pre-aligned to PDPL, NDMO Classification, and ISO 27001.
- Actively selecting design-partner Haram operations and crowd-safety authorities for a first pilot cohort.
Go-to-market
Land on a defined zone, expand to full Haram coverage
- 1Land with a design-partner Haram operations or crowd-safety authority, starting on a defined set of zones and camera feeds.
- 2Prove detection accuracy and dispatch-time reduction over a pilot season against the current manual process.
- 3Expand to full Haram and surrounding-facility coverage once zone-level results are proven.
Team
Built by operators, not just builders
The ask
Raising a seed round to reach first design-partner deployments
We're raising to fund detection-model hardening against real crowd footage, on-premise deployment tooling, and the core team through first-revenue pilot deployments.