Artificial Intelligence Solution
for Houston-based Startup


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.


  • 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


The AI solution crafted by App Maisters encompassed the following key components:

  1. Swift Search Engine: A Google-type search engine was implemented, delivering results instantaneously, ensuring seamless user experience.
  2. 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.
  3. 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.