Innovations

The Auto-Standardiser

Problems addressed

Converting heterogeneous, messy databases into European industry-standard schemas (GTFS, FIWARE) is extremely slow, complex, expensive, and prone to human entry errors.

Unique Value Proposition

Automatically maps and translates datasets into recognized European standards using linguistic machine-learning algorithms paired with supervised Human-in-the-Loop (HiTL) validation

Validated UC & Key Performance Benchmark

(Where was it tested, and what exact performance improvement or resource reduction did it achieve?)

Tested in: Internal lab testing for transport and energy.

Hard metrics:
>50% Reduction in mapping time
Supports a minimum of 3 official industry schemas across Mobility, Energy, and Green Deal sectors
Continuous ML learning rate

Target Stakeholder Segments

(Who adopts/Hands-on Users)

Data Engineers, Database Administrators, Public Transport Authorities (PTAs), Transport Service Providers (TSPs), and Corporate CTOs

Key Industry / Vertical Markets

(Where it is deployed)

Public Transport & Urban Mobility, Regional Energy Grids, Green Deal Data Spaces, and Logistics

License Model & IP and Commercial Strategy

(Open Source License)

Open Source License: EPL-2.0/Apache 2.0 for the core schema mapping algorithms

Commercial Streams: TransiTool web application SaaS; Custom schema integration fees; HiTL Supervisor-as-a-Service

Proprietary Strategy: Software Copyright; Background IP Protection

Availability

(Code Repository link)

Open Source License: EPL-2.0/Apache 2.0 for the core schema mapping algorithms

Commercial Streams: TransiTool web application SaaS; Custom schema integration fees; HiTL Supervisor-as-a-Service

Proprietary Strategy: Software Copyright; Background IP Protection

Estimated Time to Market

~1 year post-project