Artificial Intelligence Solution
Background
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.
Objective
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.
Solution
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.
Main Features Of The App
- Subscription Model: Offers tiered access based on subscription levels.
- Big Data Storage: Efficiently manages vast web data in condensed form.
- Advanced Search: AI-powered engine for precise searches using factors like sensitivity, sentiment, keywords, and more.
- Visualized Insights: Intuitive tools for clear data visualization and insights.
- Statistical Analysis: Empowers analysts with k-means, lda topic extraction, and advanced techniques.
- Industry-Tailored: Specialized insights for Oil & Gas, Finance/Banking, Healthcare.
- Predictive Analytics: Supports data-driven predictions and investment decisions.
- Customization: Users can personalize preferences and search criteria.
- User-Friendly: Intuitive interface for seamless navigation.
- Continuous Updates: Regular enhancements keep the app current and relevant.
Tools & Technology
- Backend: AWS EC2, Load balancer, Cloud watch, Amazon Elastic Beanstalk, Amazon Elastic search (big data), Amazon Apache Spark(distributed computing), AWS S3
- Languages: PHP, Python, Javascript, MySQL, JSON
- Third-Party APIs: SciKit, Scipy, PySpark, Stripe, JSON to CSV, CSV to JSON, Pandas
Result
The AI solution crafted by App Maisters encompassed the following key components:
- Swift Search Engine: A Google-type search engine was implemented, delivering results instantaneously, ensuring seamless user experience.
- Effortless Data Retrieval: The solution boasted the power of AI-driven Named Entity Recognition and scientific data extraction, catering to data scientists and analysts. This capability was achieved within mere seconds through distributive computing.
- Robust SaaS Application: The developed SaaS-based application exhibited paramount qualities of auto-scalability, security, and robustness, ensuring optimal performance even under varying workloads.
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.