Corporate & Government
We are delivering innovative solutions for leading corporations, public health authorities and government agencies. Some of our customers are on the Fortune® 100.
eCommerce Customer Reviews Optimization
The Company struggled with either one: overestimating or underestimating of the budget for products startup and products lifecycle management on the Polish market. Working for them, we prepared Machine Learning models which enables one to predict the level of sales and level of reviews in relation to multiple internal and external factors (e.g. different shops, product groups, prices, etc.) by combining business knowledge of subject matter experts with historical data. The final results (including interdependencies) are showing avg. precision prediction at the level of 90% making the company excited about the potential of the data-driven approach.
Technology: Python, JupyteR, SkLearn
The telecommunication company in Australia, besides being a telecommunication provider, is a solution provider of a strong, policy-driven security architecture – a B2B framework of clearly articulated security principles that can be enforced through defined security domains and controls, and implemented through set standards, guidelines and procedures.
Cognitum developed a tool, that is allowing encoding the knowledge of cyber-security expert. Then it is allowing customers to perform guided cyber-security health check, and after the health-check is completed, the detailed report (diagnosis) is generated allowing the customer to understand the current state of the company’s cybersecurity maturity level and understand the weak points. The estimation of the Potential Cost of the Problem is also provided.
Technology: Python, JupyteR, Knowledge Graphs, Controlled Natural Language, OWL/RDF
Clinical Decision Supporting System for the public health authority
Clinical registers are needed to perform research studies and thus to increase medical knowledge that finds its way into new and improved guidelines. Adherence to clinical practice guidelines is mandatory to increase the effectiveness of treatments and to eliminate the negative consequences of medical decisions. We organised available data into the knowledge of the diagnostic process, based on many sources like studies, publications, recommendations, so it supports doctors decisions. We also developed a central registry for collecting patient’s clinical data from over 70 oncological institutions in Poland. In production since 2016. The results were published in Expert Systems With Applications that is currently ranked number 1 in the Google Scholar h-index listed under the top publications of Artificial Intelligence.
Technology: Python, JupyteR, C#, Jena, Knowledge Graphs, Controlled Natural Language, Ontologies, SNOMED, OWL/RL reasoning
Trade Promotion Optimization
Sales analysts are responsible for providing the promotion plan for the new quarter in most of big FMCG enterprises. Currently, these plans are created manually, mostly using conventional tools like Excel that try to solve the typical TPO (Trade Promotion Optimisation) problems like: promotion strategy, effective promotion calendar, optimise budget KPIs.
Cognitum combined business knowledge of subject matter experts with historical sales data that we received. We also took into account their anomalies and outliers. Thanks to that the Solution enabled the Company to perform sales analysis across multiple products categories over time and make a prediction of sales volume in a given time frame. The solution enabled the Company to increase its accuracy in prediction by up to 10% of volume planning.
Technology: Python C#, MSSQL, R (RStudio), Python (JupyteR), Django, SPA in React/Redux
Automated Decision Making System
In order to sign a contract, CEO of the leading corporation has to analyse business situations and implement a good strategy, especially about 10m$+ contracts. CEO makes highly contextual and time-sensitive decisions that have to factor in priorities, such as risk aversion or profitability.
Cognitum has developed the Automated Decision-Making System. The core of the system combine both expert knowledge and intuition-graphs, in order to calculate the quality score of the deal/opportunity.
A.I. models wrapped in the user-friendly UI, with drag and drop editor for tuning the expert knowledge consumed by the models produce a visualisation of the results for the CEO.
Technology: C#, Python (JupyteR), Absorbing Markov Chains, Graph databases, OWL/RDF