The challenge
A legacy system was holding back the operation.
The International Foundation for Aids to Navigation supports navigation safety and marine protection. Its legacy billing platform relied on manual vessel-data imports and offered limited reporting.
Staff worked around inconsistent records and billing logic. IFAN needed better visibility and control, not another layer of spreadsheets.
TTG’s response
Rebuild MENAS LightDues around the work.
TTG designed and built MENAS LightDues on Microsoft Azure. Vessel data is imported and matched against billing criteria, with workflows allowing the team to approve or cancel movements for invoicing.
Workflows for maritime agents support certificates and communications. Power BI reporting brings vessel movements and billing history into view. Financial data can be exported for accounting rather than being re-entered as separate records. This is an export route, not direct Xero integration.
How the work changes
Data matching, decisions and reporting in one workflow.
Structured training for administrators and agents accompanied the platform, with recorded sessions available for onboarding. The published account reports more reliable data, clearer operational reporting and less manual handling.
The platform gives IFAN a more adaptable basis for managing its billing operation and supporting the organisation’s wider mission.
The reported result
Stronger control. A commercial improvement.
A 3.5% revenue uplift was reported over the first nine months after launch in TTG’s 2025 award submission.
The IFAN work was associated with two Highly Commended recognitions at the UK IT Industry Awards 2025: Sustainable Innovation of the Year and Technology Refresh Project of the Year.
A separate development strand
AI-assisted checks, with human oversight.
A separate published account describes AI-assisted sanctions checking as an enhancement in development. Its intended workflow pre-screens billing records, flags potential issues and supports staff review.
That account is a development direction, not evidence that every AI capability or its projected time savings has been achieved. It is kept separate from the platform and reported result above.