Provision National Digital Twins Programme - Data Pipelines, Analytics and Visualisation PIN

Short Description

This Notice signals BIST's intention to go to market for the provision of Data Pipelines, Analytics and Visualisation (DPAV) services in support of the National Digital Twin Programme (NDTP) and is for Market Engagement purposes only.

The National Digital Twin Programme is a BIST led programme developing trusted, secure and reusable digital twin capabilities across government and wider public sector partners. The programme develops open source technologies, interoperability mechanisms, data sharing capabilities and application-layer services to support improved decision-making through data and digital technologies.

Description of the Scope

NDTP is seeking to engage with suppliers capable of providing specialist Data Pipelines, Analytics and Visualisation (DPAV) services. The requirement will support the design, development, testing, deployment and continuous improvement of data-driven applications, analytics products, visualisation tools and supporting data pipelines across the NDTP portfolio.

The scope may include the development of new applications and analytical capabilities, enhancement and extension of existing NDTP applications, creation of data ingestion and transformation pipelines, integration with nodes, node nets, APIs and data services, and the delivery of user-facing dashboards, maps, visualisations, analytical tools and decision-support capabilities. Suppliers may also be required to support geospatial analysis, scenario modelling, application deployment, technical documentation and transition to operational environments.

The successful supplier will be expected to work within NDTP's open source delivery model, contributing code and associated artefacts through NDTP GitHub environments and supporting collaboration with government departments, public sector organisations, technical partners and other suppliers.

To aid BIST in developing the specification, we are interested in furthering our understanding of the market and available capabilities. In particular, we would like to hear from suppliers with experience in application development, data engineering, analytics, visualisation, open source delivery, cloud-native technologies and integration of complex data services.

Additional information: Additional Information

Please note that should we proceed to market we will use the Government Commercial Agency (GCA) Spark DPS RM6094 to undertake this procurement. Only suppliers who are registered on the Spark DPS will be eligible to participate. If this opportunity is of interest, suppliers are strongly encouraged to register as soon as possible, as applications to join the DPS are assessed independently by GCA and processing times may vary.

BIST intends to undertake the initial Spark DPS supplier filtering exercise during the week commencing 24th August. Suppliers wishing to be considered for this opportunity should ensure they are successfully registered on the Spark DPS and that their category selections align with the filters set out in Annex A before this date.

Following the filtering exercise, BIST will issue a capability assessment questionnaire to the shortlisted suppliers. Completion of the capability assessment will be a mandatory requirement in order to be considered for invitation to tender.

It is anticipated that the ITT will be published in September 2026. The contract is expected to have a value of up to £10.5 million and run until October 2029, with the option to extend for up to one additional year.

This advance notice is intended to provide suppliers with sufficient time to complete Spark DPS registration and review their selected categories before the procurement is launched.

Details can be found at https://www.gca.gov.uk/agreements/RM6094. Any queries relating to registering on the Spark DPS should be directed to GCA as BIST does not have any control over the process or requirements.

Annex A - Spark DPS Filters

Delivery Method

AI & Automation

Natural Language Processing

Predicted Analytics

Prescriptive Analysis

Engineering / Materials Science

Spatial Computing

Data

Data Presentation

Location

UK

Security

Above Official