Our Client is AI startup based in Houston to collaboratively create a SaaS-based application focused on quantitative research-driven sectors. The application’s primary function was to offer precise entity recognition and information extraction from news media and social media platforms. This innovative solution was designed with a subscription-based model to cater to the distinct needs of industries relying on data-driven insights.
The project aimed to create a tailored solution including a subscription-based PHP website, a streamlined big data repository, and an AI-powered search engine for precise data retrieval. The ultimate goal was to offer insightful statistical analyses using advanced techniques like k-means clustering and lda topic extraction. This equipped data scientists and financial analysts in sectors such as Oil & Gas, Finance/Banking, and Healthcare to make informed predictions and strategic investment choices, fostering innovation and progress within their industries.
In response to the client’s request, our objective was to deliver an all-encompassing solution. This entailed the creation of a subscription-based PHP website, necessitating the establishment of a condensed big data repository to host extensive web data. Furthermore, a sophisticated search engine was developed, enabling data retrieval based on diverse factors such as sensitivity score, sentiment analysis, keywords, authors, and other customized search criteria.
The AI solution crafted by App Maisters encompassed the following key components:
Scalable Data Storage: The solution incorporated a data storage mechanism with the capacity to securely house terabytes of data, accommodating the expanding needs of the user base.