Purchase Orders Over €20,000 Q1 2023

Spending records

Payment date^*	Supplier	Description	Kind	Amount
31 Mar 2023	Centre for Independent Living	Personal Needs Service	Purchase Order	€28,437.94
31 Mar 2023	HEAnet Ltd	Software support	Purchase Order	€20,910.00
31 Mar 2023	Hegan Biomass Ltd	Willow Harvesting	Purchase Order	€21,979.05
31 Mar 2023	HURCO EUROPE LTD	Milling Machine	Purchase Order	€77,490.00
31 Mar 2023	Jones Oil Ltd T/A Certa	Oil	Purchase Order	€21,213.15
31 Mar 2023	CITY ELECTRICAL FACTORS LTD	Equipment	Purchase Order	€20,326.24
31 Mar 2023	HEANET CLG	Computer Equipment	Purchase Order	€20,910.00
31 Mar 2023	FLUIDIGM FRANCE SARL	Equipment	Purchase Order	€21,746.40
31 Mar 2023	THOMAS FLINN & CO	Professional Services	Purchase Order	€21,969.82
31 Mar 2023	RADHARC LANDSCAPING CO LIMITED	Professional Services	Purchase Order	€22,075.75
31 Mar 2023	HEALTH DDBW LIMITED T/A HEALTH XL	Equipment	Purchase Order	€29,520.00
31 Mar 2023	SCIENTIFIC INSTRUMENTS IRELAND LTD	Equipment	Purchase Order	€30,682.05
31 Mar 2023	ONNEC IRELAND LIMITED	Computer Equipment	Purchase Order	€59,260.05
31 Mar 2023	VIVITRO LABS INC	Equipment	Purchase Order	€144,156.00
31 Mar 2023	GALWAY STATIONERY SUPPLIES T/A ULTIMATE OFFICE	Stationary	Purchase Order	€147,549.55

^* 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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