Payments over €20,000 Q4 2025

Spending records

Payment date^*	Supplier	Description	Kind	Amount
31 Dec 2025	ICT Architecture and Roadmap Forvis Mazars	Consultancy Services	Purchase Order	€88,330.00
31 Dec 2025	Technology Assessment for Monitoring and Enforcement in Ireland’s Maritime Marine Institute	Area	Purchase Order	€25,908.00
31 Dec 2025	Marine Mammal Appropriate Assessment Marine Institute	Toolkit	Purchase Order	€23,093.00
31 Dec 2025	Review of Marine Bird Disturbance and Marine Institute	Forging Ranges	Purchase Order	€22,435.00
31 Dec 2025	Development of Marine Administration Marine Institute	Viewer	Purchase Order	€110,598.00
31 Dec 2025	McCarthy Browne Consulting Technical Assessment of MAC Engineers Ltd	Applications	Purchase Order	€92,250.00
31 Dec 2025	Indecon International LTD	Review of the MAC Levy Framework	Purchase Order	€39,417.40
31 Dec 2025	ESRI Ireland	ArcGIS Licenses and Support services	Purchase Order	€33,642.96
31 Dec 2025	Codex Ltd	Office Furniture	Purchase Order	€35,756.95
31 Dec 2025	Viatel Technology Ltd	Office AV Equipment	Purchase Order	€61,777.36
31 Dec 2025	CDW	Software subscriptions	Purchase Order	€30,862.44

^* Payment date may be the end of the reporting quarter when the entity does not publish an exact date.

How to read these figures

These are reported values from published purchase order and payment records — not verified cash paid, and not total spending by this organisation. A row may be a purchase order, a payment, or another reported transaction; the source files often do not say which.

Coverage and quality vary. Some fields are blank, supplier names are free text (the same firm can appear under many labels), and descriptions are inconsistent rather than a controlled taxonomy. An amount alone says nothing about value for money and it may or may not include VAT.

Records are retrieved from each organisation’s published files such as spreadsheets, PDFs, and other formats of uneven quality. Extraction techniques (including automated parsing) can introduce gaps, misreads, or incomplete rows when source layout or quality is poor. Treat the data as a starting point for investigation, not a definitive ledger.

Here is a project that encountered similar issues