AI & R&D Technology

A Learning Algorithm.
Smarter with Every Operation.

At the core of vitaRoute lies years of R&D work. Unlike off-the-shelf solutions on the market, our algorithm learns, improves every round, and recognizes patterns unique to your operation.

Real-Time RL Learning ProcessSimulation

Epoch

1

Optimization Score

42 / 100

Learning…
977349240Start25%50%75%TargetIteration PercentageTraditional
DistanceDurationCapacityTrafficOpen HoursPriorityFuel+13

Reinforcement Learning Engine

An RL algorithm that learns from every operation — simulating thousands of scenarios in seconds to find the most efficient route.

TÜBİTAK-Funded R&D

Developed under TÜBİTAK approval with project code RL-SBRP, the algorithm was matured within Istanbul Technopark.

20+ Simultaneous Parameters

A proprietary architecture that optimizes distance, duration, capacity, traffic, priority, vehicle type and more in a single pass.

Registered & IP Protected

The algorithm structure is protected by intellectual property registration. Not open source — your competitors can't copy it.

9,847+
Training Iterations
38%
Average Efficiency Gain
20+
Optimization Parameters
3
TÜBİTAK R&D Cycles
T

TÜBİTAK-Funded

Project Code: RL-SBRP

İT

Istanbul Technopark

Technology Development Zone

IP

Registered Algorithm

IP Protected

RL

Reinforcement Learning

Self-learning engine

Roadmap

The Evolution

Each phase adds a new capability to the RL engine. We share transparently where we are and where we're heading.

Phase 1 — Core Algorithm

Q1 2026

Completed

Foundational RL architecture and first optimization loop established.

Distance & duration optimizationVehicle capacity constraintMulti-stop route orderingFacility–node matchingBasic weight balance (cost function)

Phase 2 — Constraint Engine

Q2 2026

Completed

Operational constraint layer added; multi-depot and district support.

Multi-depot & multi-facility supportPriority node managementDistrict boundary rulesTime window constraintsVehicle type classification

Phase 3 — Sector Adaptation

Q3 2026 — In Progress

In Progress

Specialized rule sets for student, personnel, VIP, and logistics sectors.

Personnel shift schedule integrationStudent transport safety rulesVIP priority & luxury vehicle matchingLogistics weight / volume optimizationDistrict-based cost analysis

Phase 4 — Real-Time Intelligence

Q1–Q2 2027

Planned

Live data streaming and dynamic re-optimization engine.

Live traffic data integrationDynamic route recalculationWeather constraint factorERP / HR system synchronizationAppointment-based time window optimization

Phase 5 — Self-Learning Engine

Q3 2027 – Q1 2028

Planned

Adaptive parameter weighting system that learns from every operation.

Driver behavior profile learningHistorical density & anomaly detectionCustomer satisfaction feedback loopMulti-objective optimization (cost + time + emissions)Adaptive parameter weights (self-tuning)

Phase 6 — Federated & Multi-Modal Intelligence

2028+

Vision 2028+

Cross-sector learning and sustainability-focused vision.

Federated learning (cross-company model sharing)Public transit modal integrationCO₂ emission minimization scoringAutonomous vehicle API readinessReal-time B2B data symbiosis

Try Our Algorithm

Test vitaRoute — born from R&D — in your own operation. Start with 50 free requests.