Request for Information (RFI) - Data Labelling

Concepts

• data services
• corsham
• ai data labelling capability
• ai data labelling processes
• ai data labelling
• data labelling capability
• data labelling
• data labelling capability vision
• this ai data labelling capability
• an ai data labelling capability

Location

Description

This Request for Information (RFI) seeks to elicit information that can assist the Defence Artificial Intelligence Centre (DAIC) to shape, support, and develop its decision-making concerning a future delivery model for the Artificial Intelligence (AI) Data Labelling capability within the Ministry of Defence (MOD). Current Situation & Data Labelling Capability Vision: At present, AI Data Labelling processes within MOD are often siloed and delivered by a mixture of Crown Servants/Contractors for specific business areas, across varying classification levels. MOD's vision is to establish an AI Data Labelling capability, empowering the rapid development and deployment of AI solutions across Defence by providing tooling and a trusted network of partners to label, enrich and analyse diverse data modalities at speed and scale. This AI Data Labelling capability will fuel the development of AI models, delivering faster insights, enhanced situational awareness, and a decisive operational advantage for a safer and more secure future. RFI Objectives: In support of the Data Labelling capability vision, this RFI seeks to help the DAIC to: - Support the development and decision making around the future delivery model for Artificial Intelligence (AI) Data Labelling capability within MOD, including in-house/outsource boundaries; - Understand the current marketplace for AI Data Labelling capability; - Make Suppliers aware of the current strategic direction that MOD is pursuing in relation to AI Data Labelling capability, and how it aligns with the current Defence Artificial Intelligence Strategy; and - Support MOD in preparing to hold an early market engagement event during the first quarter of 2025, informed by responses from the RFI. How to Participate: All interested parties are encouraged to provide their feedback and participate in this RFI by completing the following Microsoft Form: https://forms.office.com/e/cfK6ddYRG3 Please provide your responses at OFFICIAL classification only. Further background information and instructions for responding to this RFI can be found in the attached 'DAIC Data Labelling RFI Instructions & Background' document. Deadline: The deadline for participation in this RFI is Friday 17th January 2025 at 23:45 (GMT). Disclaimer: It is important to note that this RFI is for information-gathering purposes and does not guarantee that a subsequent procurement process will be run. Moreover, participation or non-participation in this RFI will not have any implication on your ability to take part in any future procurement process. Confidentiality:

CPV Codes

• 72300000 - Data services

Indicators

• Contract is suitable for SMEs.

Other Information

All responses to this RFI will be held confidentially and any commercially-sensitive information that you may wish to provide in support of your answers will not be shared with other Parties. Further Information: If you have any queries regarding this RFI or would like to provide any feedback, please contact the Buyer's Commercial Officer - Details in '4. Contact details'. Link to Microsoft Form to complete 'Defence Artificial Intelligence Centre (DAIC) Data Labelling Request for Information https://forms.office.com/e/cfK6ddYRG3 DAIC Data Labelling RFI Instructions & Background' Document 20241216_DAIC Data Labelling RFI Instructions & Background_v0.1_O.docx NB: The PDF version of the RFI questions set has been provided for ease of reference when completing the survey in the MS Forms link. Please complete the survey in the hyperlink, as per 'Section 4 - RFI Questions' in the 'DAIC Data Labelling RFI Instructions & Background' document. 20241217_Defence Artificial Intelligence Centre (DAIC) Data Labelling Request for Information_Questions Set_O.pdf