Transformation to Intelligent Automation (T2IA)
T2IA applies quantum optimization, AI, and real-time GIS to transportation — turning fleets, routes, charging, and networks into a single system that plans, adapts, and optimizes itself.
From EV charging placement and energy-aware fleet routing to airport, drone, and city-scale mobility, T2IA is building the quantum optimization layer behind next-generation transportation.
- QUBO Optimization
- Real-Time GIS
- Energy-Aware Routing
- Autonomous Mobility
Transportation is a combinatorial problem.
Modern mobility — EVs, autonomous fleets, drones, and delivery networks — depends on charging, routing, energy, and geography that all interact. Traditional planning solves each variable in isolation. T2IA solves them as one quantum optimization problem.
Location, energy, fleet demand, traffic, weather, availability, and geography are solved in isolation — producing static, brittle infrastructure.
- Location
- Energy
- Fleet demand
- Traffic
- Weather
- Availability
- Geography
A single, unified optimization problem — where every variable informs every decision, continuously, as real-world conditions change.
Six coordinated layers. One decision engine.
Raw signals from moving fleets and physical infrastructure flow up through the stack — each layer refining data into optimized mobility decisions in real time.
Quantum Optimization Engine
- QUBO formulation
- Hybrid quantum-classical optimization
- Constraint encoding
- Quantum-inspired optimization
- Solver orchestration
AI Decision Engine
- Demand prediction
- Energy forecasting
- Congestion prediction
- Anomaly detection
- Dynamic decision-making
GIS Intelligence
- Geospatial constraints
- Heatmaps
- Restricted zones
- Infrastructure mapping
- Real-time telemetry overlays
Fleet Intelligence
- Energy-aware routing
- SOC-aware dispatch
- Multi-robot coordination
- Charging scheduling
- Dynamic rerouting
Autonomous Infrastructure
- Charging pads
- Docking systems
- Sensors
- Activation / deactivation
- Load balancing & weather adaptation
Enterprise & City Integration
- Enterprise API connectors
- Fleet & OEM interoperability
- Multi-tenant deployment
- City-scale orchestration
- Third-party data integration
Physical World → Intelligence Layer → Autonomous Decisions
Quantum-Optimized Charging Pad Placement System
Transforming charging infrastructure placement from a static planning exercise into a computational optimization problem.
Q-CPPS formulates charging infrastructure placement as a constrained optimization problem and combines quantum/hybrid optimization with geospatial intelligence to identify strategically optimal locations.
Explore Q-CPPSMobility at scale is beyond classical optimization.
As transportation networks grow, routing, charging, and fleet decisions become combinatorial. The system must weigh many constraints simultaneously — exactly where quantum optimization excels.
- Thousands of candidate locations
- Fleet demand
- Energy constraints
- Travel distance
- Charging capacity
- Restricted zones
- Congestion
- Weather
- Infrastructure cost
- Reliability
- Future demand
T2IA approaches these challenges using mathematical optimization, QUBO formulations, hybrid quantum-classical approaches, and solver-agnostic orchestration.
Thousands of candidate configurations converging toward an optimized solution.
A layered intellectual property strategy.
T2IA is building a defensible technology portfolio spanning optimization, hardware, robotics, GIS, infrastructure intelligence, and distributed optimization.
T2IA Intelligence Core — protecting the intelligence stack, not just a single application.
Quantum-Optimized Charging Pad Placement System (Q-CPPS)
Core invention (current patent)
- QUBO formulation
- Hybrid quantum-classical solver
- GIS visualization
- Dynamic updating
- Autonomous fleet integration
The foundational invention that anchors the entire portfolio and every downstream layer.
Forms the foundation for all future charging-infrastructure optimization products.
- Q-CPPS
- Quantum Solver Architecture
- Distributed Quantum Optimization
- Autonomous Charging Pad + Docking
- Fleet Routing + Energy-Aware Dispatch
- GIS Optimization Platform
- Dynamic Network Self-Optimization
Executed in full, the portfolio is designed to make it difficult for competitors to replicate the stack — from optimization down to physical infrastructure.
- Using quantum optimization for charging placement
- Building similar charging pads
- Routing fleets using energy-aware logic
- Visualizing infrastructure the same way
- Scaling optimization across cities
Patent descriptions represent T2IA's technology and IP strategy and are not legal opinions regarding patentability, scope, or enforceability. Current patents are visually distinguished from future and proposed IP layers.
Where the platform is deployed.
The same engine scales from a single campus fleet to city-wide and airborne networks — here are the environments it runs in today and next.
Airports
- Autonomous ground vehicles
- Drone operations
- Charging infrastructure
- Energy-aware fleet routing
Smart Cities
- Distributed charging
- Infrastructure planning
- Traffic-aware optimization
- Autonomous mobility
Logistics
- Delivery robots
- Autonomous warehouses
- Fleet charging
- Energy-aware dispatch
Drone Networks
- Charging corridors
- Landing infrastructure
- Mission-aware routing
- Dynamic network optimization
Campuses
- University campuses
- Corporate campuses
- Healthcare campuses
- Autonomous transportation
Emergency Response
- Disaster-response fleets
- Temporary charging infrastructure
- Dynamic routing
- Infrastructure resilience
The platform, delivered as products.
The optimization engine is packaged into distinct products — from the flagship placement system to the API that powers everything.
Q-CPPS
Quantum-Optimized Charging Pad Placement System
- QUBO formulation
- Hybrid quantum-classical solver
- Constraint-aware siting
Fleet Intelligence Engine
Energy-aware routing and dispatch for autonomous fleets
- State-of-charge awareness
- Traffic-adaptive routing
- Multi-fleet coordination
GIS Decision Studio
Geospatial intelligence and infrastructure decision support
- Terrain & restricted zones
- Demand heatmaps
- Scenario visualization
Optimization API
The engine, delivered as an enterprise-ready service
- REST & streaming endpoints
- Multi-tenant deployment
- OEM interoperability
Why T2IA
Optimization First
Treat infrastructure planning as a mathematical optimization problem.
Quantum-Ready
Designed for hybrid quantum-classical optimization and evolving quantum hardware.
Geospatial Intelligence
Connect optimization directly to real-world geography.
Energy-Aware Autonomy
Integrate energy and SOC into routing and fleet decisions.
Dynamic Infrastructure
Move from static infrastructure to continuously adaptive infrastructure.
Layered IP Strategy
Build protection across algorithms, software, hardware, infrastructure, and distributed optimization.
A category that is still wide open.
The future of transportation requires more than intelligent vehicles. It requires a network capable of understanding demand, energy, geography, fleet behavior, and changing conditions — and optimizing across all of them at once.
T2IA is developing the quantum optimization and intelligence layer connecting these transportation systems.
Led by decades of engineering experience.
The people building the quantum optimization layer for transportation.
Virind Gujral
CEO & Founder, Mechanical Engineer
With over 30+ years of experience. BS in Mechanical Engineering, MBA from the UPitt, with AI and Business Strategy coursework from MIT.
Nalini Priya
Chief Operating Officer
AI and technology executive focused on Quantum AI and intelligent automation. She leads T2IA’s technology vision to transform enterprise operations through intelligent, autonomous, and scalable AI systems.
From intelligent software to self-optimizing transportation.
T2IA's long-term vision is transportation that does not simply move — but actively understands, predicts, and optimizes itself.
The next generation of transportation will be quantum-optimized.
T2IA is building the quantum intelligence required to optimize it.
Let's build the next layer of intelligent transportation.
Tell us what you are working on and our team will follow up directly.