Aleph’s technology roadmapping service delivers actionable specifications enabling our clients to develop, deploy and exploit novel data tools.
We start by understanding our clients’ decision problems – what are their key uncertainties, what information have they got access to, and what insights do they need to generate? We then draw on our knowledge and experience, which covers systems engineering, statistical modelling, information technology and machine learning, to identify a solution concept. If there are already off-the-shelf solutions that seem to do the job, we will adapt and test them. If not, we will develop and investigate novel approaches.
Our clients receive a clear, tangible roadmap, comprising technical exposition, functional specifications, architecture diagrams, pseudocode, and software demonstrators for discrete functions. If required, Aleph will work alongside our clients’ in-house or external software developers to ensure that implementation is as smooth as possible.
Case Studies
01
A government intelligence organisation asked Aleph to help them understand how the workflow of an intelligence analyst might be improved using “generation-after-next” artificially-intelligent agents.
These agents might help identify new information, alert the analyst to high-priority customer requirements, retrieve relevant existing data, and so on. Aleph started by designing an ontology describing the elements of the intelligence analyst’s workflow (entities, resources, flows and so on). This model was then used to specify the goals of an ecosystem of AI agents. Aleph built a technology demonstrator showing how these agents might use reinforcement learning approaches to self-organise and optimise the value added by the analyst. The insights generated were then used to develop a technology roadmap for the development and deployment of AI agents, enabling the customer to invest appropriately in subsequent development work.
02
Our client, a major technology firm, wanted to develop a platform that could implement and expand on crowd forecasting methods, to incorporate the identification and assessment of new and high-impact questions as well as on the delivery of probabilistic forecasts.
Aleph worked closely with our client over a two-year period to investigate and test a wide range of potential technological approaches to achieving this vision. We developed functional specifications for increasingly-sophisticated platform capabilities, culminating in a user trial of an MVP software tool, and delivered a substantially-evidenced roadmap for the tool’s development into a commercially-viable software tool.
03
Our client, a large defence organisation, had an urgent need to improve the way that data about cyber security risks, vulnerabilities, and incidents were collected and analysed.
The client’s existing processes were largely antiquated and had grown up organically over several years. Aleph started by analysing the customer’s requirements: what decisions was this data supposed to inform? This enabled us to develop an adaptable data framework that was compatible with existing processes, but could be used to enrich current data, and collate data from different sources using the same underlying framework. Working closely with the client, and a range of cyber security experts, we designed a pathway for the deployment and extension of this framework within the organisation. This included a range of additional assets (such as data pipeline architectures and schema maps) that were used to support the framework’s implementation.