Reducing time to value by 95%

Point Sigma's AI-driven analytics boosts data analytics efficiency for a UK Central Government Department.

UK Government Department

The Organisation

A newly established branch of a UK Central Government department, with an annual budget exceeding £2bn, sought to harness AI for gaining data-driven insights quickly. Partnering with ⊙-Σ, the department streamlined the analysis of complex datasets generated by various disjointed systems.

Point Sigma

Point Sigma is the world's first fully end-to-end autonomous AI-driven data analytics solution. Point Sigma empowers people to become citizen data scientists by broadening the reach of analytics to all decision-makers, creating competitive advantage.


The Point Sigma platform helped to facilitate data exploration for each of the fields in the datasets. Clicking on any of the fields generated charts with statistical significance automatically.

Senior Project Leader

The challenge

The department identified 30+ data sources that would require integration to surface relevant insights. Industry advice was that this could take three years and a budget of £150+ million. A big investment when there may be no significant insights to be discovered.

The department faced significant challenges in accessing and integrating diverse data sets, residing in siloed systems with different formats, structures, and standards. Navigating through the technical landscape posed hurdles, along with data quality issues and the complexity of manual validation. They identified that advanced analytics capabilities were required to rapidly (and cheaply) deliver meaningful insights, coupled with the challenge of transforming these insights into graphical visualisations for effective communication within the large-scale government operation.

Point Sigma

Point Sigma is a data analytics and business intelligence platform that configures itself using Artificial Intelligence instead of human experts. Point Sigma uses a novel type of AI, called Artificial Curiosity™ that works


in a similar way to how humans find interesting insights in data. It works out from raw data, all the way to insights, how to combine the relevant data processing steps to produce the most interesting results.

The solution

Point Sigma's Data Curious AI-driven platform proved instrumental in addressing these challenges. Unlike traditional tools, Point Sigma's platform utilises AI for automatic data preparation, structuring and understanding, allowing non-technical users to explore insights within minutes of data upload. This significantly reduced the dependency on technical teams, reducing the time to insight from three months to three days. The platform enabled users to browse auto-discovered insights by source, type and relevance, providing a broad view or zooming in on specific aspects of the data. Users could explore related patterns for different perspectives on the data, facilitating unanticipated insights.

The Augmented Insights Management (AIM) platform allowed non technical staff to access visualised data from the beginning of the project without having to wait months for the data to be manually wrangled into shape. In addition to auto-discovered patterns, users had the flexibility to create bespoke graphs, accelerating the process of reaching conclusions and informing other parts of the organisation for prompt action.

The impact

  • Deploying an AI-driven platform to wrangle the raw data from disparate systems reduces time to value by 95%. Results in three days, not three months.
  • Once Point Sigma's AI-driven analytics platform has wrangled the data, and its Augmented Insights Management (AIM) environment enables quick and easy data exploration for non-technical users.
  • Point Sigma's transparent use of AI to understand, structure and extract insights from data fitted well with the department's own AI strategy and was received positively by its AI oversight board.
  • Insights discovered by users and suggested by the platform ranged from data quality issues, known and unknown correlations, and the main themes for the department's focus areas.