--- title: "DSIT - Revelio Labs" ocid: "ocds-h6vhtk-06db98" canonical_url: "https://d3tenders.com/contract/?ocid=ocds-h6vhtk-06db98" markdown_url: "https://d3tenders.com/contract/ocds-h6vhtk-06db98.md" json_url: "https://d3tenders.com/contract/ocds-h6vhtk-06db98.json" source: "Find A Tender Service" current_stage: "Award" buyer: "DEPARTMENT FOR SCIENCE, INNOVATION & TECHNOLOGY" published: "2026-08-04" --- # DSIT - Revelio Labs Buyer: DEPARTMENT FOR SCIENCE, INNOVATION & TECHNOLOGY Current stage: Award OCID: ocds-h6vhtk-06db98 [View canonical contract page](https://d3tenders.com/contract/?ocid=ocds-h6vhtk-06db98) [Download OCDS JSON](https://d3tenders.com/contract/ocds-h6vhtk-06db98.json) ## Summary The Department for Science, Innovation & Technology (DSIT) has initiated a direct award contract with Revelio Labs, a US-based supplier, for provision of workforce intelligence data. This procurement is under the legal framework of the UK Public General Acts 2023/54, targeting the AI adoption impact on the labour market and skills dynamics. With a contract value of £80,000, the agreement is set for a 12-month period starting on 24th August 2026, with the procurement process currently at the award stage. The project aims to support DSIT's AI Security Institute research programme, focusing on providing empirical benchmarks and analytical insights that inform future UK workforce and education policy. This procurement effort offers a significant opportunity for businesses operating in data supply services, particularly those specialising in workforce analytics and artificial intelligence. Firms with capabilities in providing detailed workforce intelligence data can find similar contracts beneficial for growth by supporting high-level governmental research initiatives. The focus on AI adoption and its implications on labour markets presents a niche yet expanding market, ideal for businesses that are at the forefront of data-driven insights and analytics. Such projects not only provide immediate financial benefits but also strengthen the supplier’s reputation and portfolio, positioning them competitively in future governmental tenders. ## Notice This procurement is a proportionate, time-limited 12-month data access arrangement designed to meet an urgent evidence need for DSIT/AI Security Institute. The requirement is for access to an existing commercial workforce intelligence dataset, rather than consultancy or bespoke analytical services, and will enable DSIT to test, validate and strengthen the evidence base on AI adoption and labour market impacts. The arrangement is capped at PS80,000, with no extension options or open-ended spend commitment, and will be managed within existing programme budgets and governance. DSIT's AI Security Institute is looking to direct award Revelio Labs for workforce intelligence data to support DSIT's research programme on AI adoption and its impact on the labour market, with a particular focus on skill dynamics, workforce composition, and career trajectories. Objectives: 1. Understand how AI adoption reshapes skill demand and supply at the firm level. By acquiring granular, firm-level workforce data (job postings, employee profiles, skill taxonomies, and workforce flows), DSIT's AI & the Future of Work Unit will measure how skill composition evolves at firms actively adopting AI compared to those that are not. 2. Provide an empirical benchmark for AI exposure measurement. Workforce intelligence data enables DSIT to identify which skills actually co-occur with AI adoption at the firm level, providing ground-truth validation of theoretical classifications and improving future measurement frameworks. 3. Replicate and extend published research on early-career labour market outcomes. To credibly replicate, validate, and extend these estimates for UK policy purposes, DSIT requires access to comparable data of equivalent granularity and structure. 4. Inform UK workforce and education policy. The evidence generated will directly support policy advice on (examples): which skills retraining programmes should prioritise; where skill gaps are emerging; how curricula should adapt to changing employer expectations; and whether skill dynamics can serve as leading indicators of broader labour market disruption. 5. Establish early warning capability. By tracking skill shifts that may precede larger employment effects, DSIT aims to build an analytical early warning system that identifies workforce risks before they become visible in aggregate official statistics. The Arrangement is intended to be entered into by the Secretary of State for Science, Innovation and Technology. It is anticipated that the rights and liabilities of the Secretary of State for Science, Innovation and Technology, including those arising under this Arrangement once executed, will in due course transfer to the Secretary of State for the Cabinet Office pursuant to an Order in Council (secondary legislation) made under section 2 of the Ministers of the Crown Act 1975. ### Procurement Information We are looking to direct award this contract after a market engagement EOI was conducted under the Sparks DPS with no viable supplier who can conduct this requirement. The EOI responses were moderated and reviewed by the department's data aquisition team and they confirmed given the urgency of this requirement, we should direct award this tender following no suitable suppliers. This tender will aid the work that is carried out by the AI Security Institiute (AISI) in DSIT. The AISI team found a supplier in the US (Revelio Labs) who are able to carry out these requirements and this was also reviewed by DSIT's data aquisition team which they were satisfied with. We will advise Revelio Labs to join a DPS Framework. ## Key Details | Field | Value | | --- | --- | | Publication source | Find A Tender Service | | Latest notice | https://www.find-tender.service.gov.uk/Notice/073830-2026 | | Notice type | UK5 - Transparency Notice | | Procurement type | Standard | | Procurement category | Services | | Procurement method | Direct | | Procurement method details | Direct award | | Tender suitability | Not specified | | Awardee scale | SME | | All stages | Award | ## Dates | Field | Value | | --- | --- | | Publication date | 4 Aug 2026 | | Submission deadline | Not specified | | Future notice date | Not specified | | Award date | 4 Aug 2026 | | Contract period | 23 Aug 2026 - 23 Aug 2027 | | Recurrence | Not specified | ## Values | Field | Value | | --- | --- | | Tender value | Not specified | | Lots value | Not specified | | Awards value | £80,000 | | Contracts value | Not specified | ## Status | Field | Value | | --- | --- | | Tender status | Complete | | Lots status | Complete | | Awards status | Pending | | Contracts status | Not specified | ## Buyer | Field | Value | | --- | --- | | Main buyer | DEPARTMENT FOR SCIENCE, INNOVATION & TECHNOLOGY | | Locality | LONDON | | Post town | South West London | | Postcode | SW1A 2EG | | Country | England | | ITL 1 | TLI London | | ITL 2 | TLI3 Inner London - West | | ITL 3 | TLI35 Westminster and City of London | | Local authority | Westminster | | Electoral ward | St James's | | Westminster constituency | Cities of London and Westminster | | Delivery location | Not specified | ## Supplier | Field | Value | | --- | --- | | Number of suppliers | 1 | | Supplier names | REVELIO LABS | ## CPV Codes ### Divisions - 72 - IT services: consulting, software development, Internet and support ### Codes - 72319000 - Data supply services ## Release History - 4 Aug 2026 at 14:50 - Award - UK5 - Transparency Notice - https://www.find-tender.service.gov.uk/Notice/073830-2026 ## Documents - https://www.find-tender.service.gov.uk/Notice/073830-2026 4th August 2026 - Transparency notice on Find a Tender ## Notice URLs - https://www.legislation.gov.uk/ukpga/2023/54/contents ## Provenance This Markdown file is an alternate public rendering of the D3 Tenders contract record. The canonical page is https://d3tenders.com/contract/?ocid=ocds-h6vhtk-06db98. The underlying structured data is available as OCDS JSON at https://d3tenders.com/contract/ocds-h6vhtk-06db98.json.