U.S.-based technology firm Sociologix says it is building RIYDE, an AI-driven ride-sharing and on-demand delivery platform for Guyana, positioning it as a full-feature “super-app” designed to improve mobility access, expand last-mile commerce, reduce transportation emissions, and direct a portion of proceeds toward rainforest protection.
Guyana is widely described as a high-forest-cover country. The Forest Carbon Partnership Facility (FCPF) reports Guyana has about 18.4 million hectares of forest, representing ~85% of national land area. Global Forest Watch reports that in 2020, ~89% of Guyana’s land area was natural forest (methodology-dependent). Guyana’s Low Carbon Development Strategy (LCDS) 2030 emphasizes maintaining forest assets and describes Guyana as having exceptionally high forest cover and forest retention.
Sociologix says RIYDE is being built to include the complete set of features typically found in leading regional ride-hailing and delivery platforms: on-demand rides, scheduled rides, multi-stop trips, pooled rides, real-time driver tracking and ETAs, in-app communications, digital receipts, and a driver earnings and incentives suite. The delivery marketplace is expected at launch to support prepared meals, groceries, non-prescription/OTC pharmacy items, and selected consumer electronics, with the platform dispatching both RIYDE-managed drivers and third-party couriers connected through merchant partners.
Sociologix also disclosed a commercial policy target under which up to 80% of platform profit would be allocated to drivers and couriers (through higher per-trip payouts and incentive pools), with ~20% retained to fund the RIYDE ecosystem—product development, safety operations, customer support, insurance and compliance, and sustainability reporting. The company described this as a “driver-first” model intended to increase take-home earnings and stabilize supply.
AI “does the heavy lifting”
The firm says its proprietary AI layer is designed to continuously optimize:
- Dispatch and matching to minimize pickup time and empty miles (“deadheading”)
- Pooling feasibility to increase average occupancy on compatible corridors
- Eco-routing to reduce congestion, idling, and stop-and-go driving patterns
- Risk and fraud controls (e.g., GPS spoofing detection and anomaly flags)
- Support automation to shorten resolution times and reduce operating overhead
For emissions benchmarking, planners frequently reference the U.S. Environmental Protection Agency’s estimate that an average passenger vehicle emits about 400 grams of CO₂ per mile (≈ 249 g CO₂ per km) as a conservative baseline before adjusting to local fleet data.
Forecast impact (modeled planning ranges; to be calibrated post-launch)
Sociologix provided modeling ranges rather than audited results, noting outcomes will depend on adoption of pooling, delivery density, and driver utilization.
Illustrative Year-1 Georgetown-led ramp (average run-rate scenario)
- 3,000 rides/day and 1,500 deliveries/day
- Distance assumptions: ~6 km/ride and ~5 km/delivery
- Efficiency improvement target: ~8–18% reduction in modeled CO₂e per service-km (pooling + deadhead reduction + eco-routing + smoother driving)
Under those assumptions, annual baseline tailpipe emissions are approximately ~2,318 tCO₂/year, implying ~185–417 tCO₂/year avoided (modeled).
Illustrative Year-3 national scale scenario
- 20,000 rides/day and 10,000 deliveries/day
- Efficiency improvement target: ~12–28% reduction in modeled CO₂e per service-km
That yields approximately ~15,450 tCO₂/year baseline and ~1,854–4,326 tCO₂/year avoided (modeled), subject to local calibration.
Sociologix says it plans to publish a monthly “Green Ledger” summarizing trip volumes, modeled CO₂e savings, and conservation allocations. The company positioned the program as aligned to Guyana’s LCDS 2030 emphasis on preserving forest assets and channeling low-carbon value into development priorities. Recent UNFCCC REDD+ documentation also describes Guyana as a high-forest-cover country with very low deforestation rates under its reporting framework.
Sociologix stated the initiative is led by Gaurav Masram, described as an award-winning technology designer and pioneer, serving as Lead Innovator for platform architecture, AI dispatch optimization, safety engineering, and sustainability measurement.
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