Tools
Aleph Insights designs and builds analytical software for problems that can’t be solved by off-the-shelf tools. We work with our network of partners to deliver software solutions that meet your data analytics needs. Aleph Insights specialises in the design of software solutions relating to data structuring, risk modelling, probabilistic forecasting and a range of other analytical functions. We work iteratively using agile development to make sure our tools can be fully integrated into your organisational workflow.
Related Case Study
Risk model for the assessment of cyber risk
- Client:Ministry of Defence
- Years:2016 - 2018
On behalf of the Ministry of Defence (MOD), we developed a risk model for the assessment of cyber risk. In conjunction with our partner, Riskaware, designed the software tool which enabled the risk model to be operated by MOD analysts. This software tool and the model on which it is based now forms the foundation of the MOD’s developing cyber risk assessment method.
Related Case Study
Risk visualisation tool
- Client:Cabinet Office
- Years:2018 - 2019
Aleph Insights was commissioned by the Cabinet Office's Civil Contingencies Secretariat to build a data visualisation tool to support their emergency planning. The tool captured, structured and then visualised complex data regarding a large number of risks and response capabilities, highlighting areas where resources should be focused. This is now in use by the Cabinet Office and other government departments and is being used to support strategic planning for a broad range of strategic risks.
Related Case Study
Project MIDGARD
- Client:Defence Science and Technology Laboratory
- Years:2021 - 2022
Project MIDGARD entailed the development of a simulated cyber defence agent to test ways in which an organisation's cyber defence policies could adapt to real-world conditions described by sparse data. Working with the University of Liverpool, Aleph developed an autonomous agent based on a Gaussian process model, which was able to learn about the value of different information channels by observing user performance on a bespoke air defence radar game. This enabled defensive cyber policies to be tuned to real-world conditions, improving outcomes.
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Pythia
- Client:Defence Science and Technology Laboratory
- Years:2021 - 2022
Aleph Insights implemented a series of machine learning approaches to support intelligence analysts and geopolitical forecasters. A proof of concept was delivered and initial trialling conducted relating to the efficacy of these approaches. This work resulted in a number of successful demonstrations which are subsequently being developed to support the intelligence analysis function.
Related Case Study
Real-World Data for Autonomous Cyber Defence
- Client:Defence Science and Technology Laboratory
- Years:2021 - 2022
Aleph Insights developed a simulated cyber defence agent to test ways in which an organisation's cyber defence policies could adapt to real-world conditions described by sparse data. Working with the University of Liverpool, Aleph developed an autonomous agent based on a Gaussian process model, which was able to learn about the value of different information channels by observing user performance on a bespoke air defence radar game. This enabled defensive cyber policies to be tuned to real-world conditions, improving outcomes.
Related Case Study
Human Machine Interface Project
- Client:Defence Science and Technology Laboratory
- Years:2019 - 2020
Dstl commissioned Aleph Insights to develop a range of evidence-based content and analytical methods to investigate the Defence implications of emerging human-machine interface technologies. This required us to develop an interactive software tool which presents a series of innovative data visualisations, including projected technology timelines, taxonomies and convergence patterns. It also involved the design and implementation of an analytical approach for assessing the suitability of new technologies to different tasks.