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Official procurement procedure
Feasibility of applying machine learning to the evaluation of irregular migration interventions
Feasibility study
advisory service
analysis
UK
Published value
Not published
Submission deadline Not published
Lots published1
Procurement Executive Summary
AI & Search Synopsis
Generated from official OCDS record
Tenderline Synopsis: Home Office: "Feasibility of applying machine learning to the evaluation of irregular migration interventions". Published status: complete. Published value: Value not published. 1 published lot. Submission deadline not published. See the official notice for participation instructions.
| Contracting Authority | Home Office | Scope & Categories | Not published | Submission Window | complete No deadline published |
|---|---|---|---|---|---|
| Submission Gateway | Direct notice route | Legal Basis & Regime | Standard procurement | Estimated Value (exc. VAT) | Not published |
Bidder Intelligence · Authority Profile: Home Office
Market Analytics
Derived from OCDS awards & bid statistics
Published history for Home Office. These figures describe retained records, not a forecast of bids or a measure of buyer bias.
Published-to-award variance
Not availableInsufficient comparable data
Competition Density
7.4Bids / Report
Supplier ConcentrationNo estimate
Insufficient attributable awardsNo concentration estimate availablePayment Terms
Check noticePublished terms
Coverage: 115 active published awards; 109 bid reports (which may be per lot). Supplier values exclude multi-supplier awards, frameworks and DPS, and use GBP only. They are published award values, not payments. Published-to-award variance compares single-lot, single-award, single-supplier GBP procedures with explicitly non-framework/non-DPS status; increases remain in the average. Unpublished data stays unknown. Awarded suppliers are winners, not all bidders.
Procedure terms
Contracting AuthorityHome Office | Procedure methodNot published | Procurement categoryNot published |
Statuscomplete | Framework / DPSNot published | CompetitionNot published |
Above thresholdNot published | Legal basisNot published | Tender period startsNot published |
Clarification deadlineNot published | Electronic submissionNot published | Submission languagesNot published |
Published10 May 2024, 14:42 BST | Last source update10 May 2024, 14:42 BST | Recurring procurementNot published |
ClassificationFeasibility study, advisory service, analysis | ||
Delivery area UK | ||
OCIDocds-h6vhtk-0458ca | ||
What is being bought
This contract is for the feasibility of AI techniques in research.
What changed
From the official release history
- Status changed to complete
10 May 2024, 14:42 BST - Official notice release published
10 May 2024, 14:42 BST - Buyer information updated
10 May 2024, 14:42 BST
Lots and requirements (1)
Published by the contracting authority
- Lot 1 · #1Individual lot title not publishedcancelledPublished valueNot publishedThis contract is for the feasibility of AI techniques in researchContract periodNot publishedEligibilityNot publishedOptions / renewalNot published
Timeline
- Procedure published
10 May 2024, 14:42 BST - Award active
Not published · Not published - Contract active
Signed 26 Mar 2024, 00:00 GMT · £119,591
Commercial outcome and competition
Awards University of Catania, University of Southampton Not published · Not published · active |
Contracts Feasibility of applying machine learning to the evaluation of irregular migration £119,591 · signed 26 Mar 2024, 00:00 GMT · active |
Bid statistics bids: 2 (lot 1) electronicBids: 2 (lot 1) foreignBidsFromEU: 1 (lot 1) |
Buyer and organisations in this procedure
Home Office
Contracting authority GB-FTS-1007Documents (0)
Official links; attachments are not copied
No linked documents are published
Related procedures (0)
No related procedures published
Planning and rationale
Planning budgetNot published |
No-engagement rationaleNot published |
Procedure rationaleCapable suppliers were researched and approached, a competition between interested suppliers was ran. The most economically advantageous supplier was then awarded the contract. |