Rasid · Pitch Deck
Aviation · RAMP & TERMINAL VISION
Rasidرصد الساحة والصالات
Turn the cameras you already have into turnaround timers, queue counters, and ramp-safety alerts.
neuriya.ai — Sovereign, Arabic-first enterprise AI
Problem
Ground and terminal operations still run on stopwatches and guesswork
- Turnaround milestones — chocks-on, door-open, catering, fueling, pushback — are timed manually by ramp agents with a stopwatch and radio call, if they're timed consistently at all.
- Security, check-in, and passport-control queues are estimated by staff on the floor rather than measured, making it hard to right-size staffing during Hajj, Umrah, and summer peaks.
- Ramp-safety incidents — FOD-risk incursions, vehicle-to-aircraft proximity, missing PPE — are typically caught after the fact in an incident report, not prevented in real time.
- Airports already operate large CCTV estates, but that footage is used for security replay, not turned into operational data, and buying new sensors is a slow, expensive procurement cycle.
Solution
Existing CCTV becomes turnaround timers, queue counters, and safety alerts
Product
Rasid in action
How it works
From first touch to outcome
Connect
Point Rasid at existing apron and terminal camera feeds — no new cameras or wiring.
Detect
Computer-vision models timestamp turnaround milestones, gate events, and queue lengths automatically.
Alert
Ramp-safety violations and abnormal queue build-ups trigger alerts to ops and security teams in real time.
Analyze
Turnaround and queue data roll up into performance dashboards for every stand, gate, and terminal zone.
Market
Sizing the opportunity
- TAM — $1.6B. MENA airport computer-vision & ramp/terminal analytics market
- SAM — $140M. Saudi airport CCTV-based ramp and terminal analytics
- SOM — $10M. 3-year obtainable share via design-partner airports and ground handlers
Saudi airports face record passenger volumes from Hajj, Umrah, and Vision 2030 tourism targets, and are under pressure to cut turnaround times without a proportional increase in ramp and terminal headcount — making analytics on already-installed cameras an easy budget case.
Business model
How Rasid makes money
Per-stand / per-camera analytics license
Subscription priced by the number of stands or camera feeds under active monitoring.
Per-airport terminal-analytics subscription
Recurring fee for queue and terminal-flow dashboards across security, check-in, and passport control.
Implementation & calibration fee
One-time fee for camera-feed integration and site-specific model calibration.
Revenue streams
Where the revenue actually comes from
Competition
Where we win
Our edge
- Runs on the camera estate airports already have — no new hardware procurement cycle, fastest path to a pilot.
- On-premise, sovereign inference — video never leaves the airport network, satisfying PDPL and NDMO requirements CV vendors abroad can't match.
- Aviation-specific model library for turnaround milestones, ramp-safety zones, and gate events, purpose-built rather than adapted from retail or security CV.
- Founding team combines Saudi ground-operations experience with computer-vision engineering.
Traction
Early validation, built for pilot readiness
- Full ramp and terminal analytics product experience designed and built end-to-end: turnaround timing, gate-event detection, queue analytics, ramp-safety alerting.
- Architecture pre-aligned to GACA, IATA AHM, PDPL, NDMO Classification, and ISO 27001.
- Actively selecting design-partner airports and ground handlers for a first pilot cohort.
Go-to-market
Land on a handful of stands, expand to full apron and terminal coverage
- 1Land with 1-2 design-partner airports or ground handlers, starting on a handful of stands and camera feeds.
- 2Prove turnaround-time and queue-accuracy gains over a pilot quarter, then expand to full apron and terminal coverage.
- 3Expand via GACA and ground-handling-company relationships across additional terminals and stations.
Team
Built by operators, not just builders
The ask
Raising a seed round to reach first airport and ground-handler pilots
We're raising to fund aviation-specific computer-vision model development, on-premise deployment tooling, and the core team through first-revenue pilot deployments.