Purchase Orders Over €20,000 Q1 2026

Spending records

Payment date^*	Supplier	Description	Kind	Amount
31 Mar 2026	DELL (IRELAND)	Purchase order over €20,000	Purchase Order	€44,201.28
31 Mar 2026	DELL (IRELAND)	Purchase order over €20,000	Purchase Order	€20,668.87
31 Mar 2026	DELL (IRELAND)	Purchase order over €20,000	Purchase Order	€62,030.13
31 Mar 2026	DELL (IRELAND)	Purchase order over €20,000	Purchase Order	€31,717.56
31 Mar 2026	DELANEY COMMERICALS LTD	Purchase order over €20,000	Purchase Order	€24,600.00
31 Mar 2026	CYGNET ELECTRONICS TA INTERTRONICS	Purchase order over €20,000	Purchase Order	€35,790.08
31 Mar 2026	CREATIVE TECHNOLOGY (AUDIO VISUAL) IRELAND LTD TA CT-IRELAND	Purchase order over €20,000	Purchase Order	€21,521.72
31 Mar 2026	CONCEPTION X LTD	Purchase order over €20,000	Purchase Order	€32,000.00
31 Mar 2026	COLEMAN ELECTRONICS LTD	Purchase order over €20,000	Purchase Order	€24,796.35
31 Mar 2026	CLEAN IRL REFUSE & RECYCLING CO	Purchase order over €20,000	Purchase Order	€39,725.00
31 Mar 2026	BARKER BRETTELL LLP	Purchase order over €20,000	Purchase Order	€24,600.00
31 Mar 2026	AGILENT TECHNOLOGIES IRELAND LTD	Purchase order over €20,000	Purchase Order	€29,172.49
31 Mar 2026	AFARA ED LTD	Purchase order over €20,000	Purchase Order	€49,200.00
31 Mar 2026	2INTO3	Purchase order over €20,000	Purchase Order	€24,600.00

^* 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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