Although the company was already using AI in its services and processes, the company wanted an external view on their approach that identify potential issues , possible mitigations and best approach recommendations.
THE SOLUTION
We designed and delivered a workshop for both executives and employees to harness the usage of the company data to maximise the full potential and mitigate the identiļ¬ed issues. The focus of the workshop was to teach the best approach on how to use and not to use AI solutions on company data so that ROI is maximised and mistakes are mitigated.
The problem
The investment firm attempts to make decision-making as objectively as possible combining traditional and alternative sources of data. For this particular case, the firm wanted to capture emerging innovation trends across industries by integrating and analyzing 'live information' from websites and financial transactions.
THE SOLUTION
We developed a solution that extracts detailed information of companies' products and track their evolution over time, potentially leading to the identification of new market trends. The solution heavily uses custom LLMs models and neural networks algorithms on the data scraped from the companies' websites and from the transactions.
The problem
There is abundance of restaurants and entertainment choices nowadays and consumers are usually overwhelmed. Eezy wanted to recommend venues based on personality of each users rather than reviews.
THE SOLUTION
We build a solution based on both the actual mood of the person when he/she open the app and his/her personality: the machine learning engine matches this information with entertainement options in tune with that in real time.
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