Matching latency
Match decisions take seconds during peak; riders cancel, drivers idle, both sides churn. Latency is the unit economic, not a UX detail.
Ride-hailing, food delivery, home services, on-site repair, every on-demand category lives or dies on real-time matching, ETA honesty and surge logic that customers tolerate. We engineer the dispatch engine, driver and provider apps, and the payment flows behind them to perform under Riyadh-traffic, payday-spike reality.
Customers request a service by location and time in a few taps.
The nearest available provider is matched and dispatched live.
Rated, paid and settled, all in-app.
Service is completed, rated and paid, settled in-app.
Instant requests, provider matching, live ETA, in-app pay and ratings, one platform built end to end.
The architectural shortcuts that look fine in a pilot and become structural problems at city scale.
Match decisions take seconds during peak; riders cancel, drivers idle, both sides churn. Latency is the unit economic, not a UX detail.
Optimistic ETAs drive the cancel rate. Honest ETAs powered by traffic, driver state and historical patterns drive retention.
Driver/provider licences and Qiwa status expire silently. The platform discovers it when a regulator does.
Static surge multipliers anger users without serving real supply scarcity. Demand modelling is engineered, not heuristic.
Per-trip payouts to drivers, restaurants, partners, tax, split incorrectly once and the support cost compounds for months.
No SOS, no journey monitoring, no reviewable evidence after an incident. One viral story is enough to stall growth.
Production modules across ride-hailing, delivery and home-services engagements.
Sub-200ms matcher with geo-sharded supply pools, retry handling and explainable assignment for support and audit.
Live traffic, road-network state and historical demand feed an ETA model calibrated to the corridor, not the average.
Demand-supply elasticity with transparent surge signalling, cooldowns and price-ceilings that protect customer trust.
Battery-aware, low-data, offline-tolerant native app with Nafath onboarding, document expiry and earnings transparency.
Per-trip ledger postings, multi-party splits, ZATCA-compliant invoicing and reconciled payout flows for drivers and partners.
SOS, journey sharing, anomaly detection on routes and timings, plus a case-management surface for the safety team.
All three. The matching, dispatch, payments and safety modules are the same architecture, what changes is the supply-side onboarding, asset types and the trip lifecycle. Cross-category platforms benefit most from this.
Yes, we engineer for surge, not for steady state. Geo-sharded matchers, async pricing recompute and elastic infra mean the platform degrades gracefully rather than collapsing on the night that matters.
Provider onboarding is wired into Nafath identity and Qiwa employment status, with TGA category checks where required. Document expiry monitoring keeps the active fleet compliant, automatically.
Each completed trip generates a ZATCA Phase 2-compliant e-invoice automatically, with credit notes for cancellations and refunds. No manual issuance, no end-of-month surprises.
Tell us where matching, pricing or payouts strain today. We'll map the engine that handles peak day without paging the founders.
We usually reply within one business day