Payments Over €20,000 Q4 2023

Spending records

Payment date^*	Supplier	Description	Kind	Amount
31 Dec 2023	Circle K	Heating Oil	Purchase Order	€20,265.03
31 Dec 2023	Datapac Ltd.	Managed Print/Helpdesk Support	Purchase Order	€25,950.25
31 Dec 2023	Viridian Energia	Electricity Supply	Purchase Order	€25,370.93
31 Dec 2023	EA / AD Therapeutic Services Limited	AON Assessments	Purchase Order	€76,150.00
31 Dec 2023	Nifti Business	Lease of electric cars	Purchase Order	€22,174.03
31 Dec 2023	Edward O'Loughlin	General Maintenance/Refurb works	Purchase Order	€31,281.00
31 Dec 2023	Motum Transport Ltd	Contract Transport Services	Purchase Order	€64,820.00
31 Dec 2023	ORI Recruitment Ltd	Recruitment Services	Purchase Order	€39,696.75
31 Dec 2023	Petrogas Group Ltd Applegreen	Vehicle Fuel	Purchase Order	€49,247.63
31 Dec 2023	Tapeford Ltd.	Property Rental	Purchase Order	€24,600.00
31 Dec 2023	Active Electrical/Norman Glynn Electrical Limited	Electrical Maintenane/Alarm Maintenance	Purchase Order	€36,568.35
31 Dec 2023	Aon MacDonalgh Boland Insurance	Insurance	Purchase Order	€97,380.10
31 Dec 2023	Burke Bros Joinery Ltd.	Installation of Fire Doors	Purchase Order	€96,794.20
31 Dec 2023	Besure Building & Property Maintenance Limited	Refurbishment Works	Purchase Order	€61,823.00

^* 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.

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