AI Infrastructure for Modern Transportation Systems
LYNQR is an AI‑native infrastructure platform built on the WHEELS framework—connecting vehicles, infrastructure, operations, and policy so transportation systems can be planned, operated, and evolved at metropolitan scale.
The WHEELS Framework in Practice
A layered platform that unifies multimodal data, orchestrates AI workflows, and executes decisions across edge and cloud—while staying policy- and audit-ready.
Data Fabric
Ingests, normalizes, and links multimodal datasets across vendors, agencies, fleets, and infrastructure.
- • Connectors for fleet, AVL/CAD, CMMS, IoT, roadway, payments, and planning data
- • Semantic mapping layer (technical + policy)
- • Batch + streaming support
Intelligence Layer
Task-specific AI agents and models coordinate decision workflows across planning, operations, and maintenance.
- • RAG-ready knowledge foundation (without exposing proprietary internals)
- • Optimization and simulation loops
- • Human-in-the-loop approvals and audit logs
Execution Layer
Runs decisions where they matter—at the edge for immediacy and in the cloud for deep analysis.
- • Edge telemetry + event detection
- • Real-time monitoring and alerts
- • Continuous improvement through feedback loops
Governance & Trust
Policy-aware controls for safety, explainability, and responsible AI adoption in public and private environments.
- • Data access controls and tenant separation
- • Traceable decisions and model explainability hooks
- • Security-first posture (MFA, least privilege, logging)
Products Built on WHEELS
WHEELS enables multiple products and domains to be composed on a shared AI-native foundation. FleetLynq is the first product; others extend across the complete trip lifecycle.
Complete Trip Intelligence
Orchestrates end-to-end trips across modes, systems, and policies—integrating planning, real-time conditions, and traveler context.
Traveler Experience & Information
Delivers consistent, policy-aware traveler information across apps, channels, and disruptions—grounded in system state.
Connected Vehicle & Device Intelligence
Normalizes and operationalizes telemetry from vehicles and devices to support diagnostics, awareness, and downstream decisions.
Fleet & Asset Intelligence (FleetLynq)
Applies WHEELS to fleet health, asset management, and lifecycle optimization—moving from reactive to proactive maintenance.
Operations & Multimodal Command
Provides a unified operational view across modes and agencies for coordination, response, and performance monitoring.
Wayfinding & Network Context
Integrates spatial context, wayfinding assets, and localization to ground decisions in the physical transportation network.
Architecture
A high-level view of how LYNQR connects edge, data, intelligence, and applications—without revealing proprietary implementation details.
About LYNQR and WHEELS
LYNQR is built for the operational, regulatory, and data realities of transportation—where vendor fragmentation, legacy systems, and policy constraints make generic AI approaches fail.
Our approach focuses on interoperability, governance, and modular intelligence so agencies and operators can evolve capability without ripping and replacing systems.
- • A transportation data fabric with semantic + policy mapping
- • Agent orchestration for planning, operations, maintenance
- • Edge–cloud runtime for real-time and long-horizon intelligence
- • Governance and auditability for responsible AI adoption
Request early access
Share a few details and we’ll follow up with next steps. We prioritize pilots that demonstrate measurable ROI and system interoperability.