Case Studies
Enhancing Cybersecurity and Network Efficiency with AI at a Cybersecurity Consultant Firm
The firm faced the dual challenge of protecting clients against increasingly sophisticated cyber threats and optimizing network traffic efficiency for their lighthouse customers. The need for advanced, predictive solutions to detect anomalies and recommend optimal network configurations was critical to maintaining their competitive edge and ensuring client satisfaction.
The Solution
Cyber Defense and Anomaly Detection: The firm developed a cutting-edge system utilizing a mix of supervised, unsupervised, and generative learning models, including Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), Transformers, Variational Autoencoders (VAE), and Temporal Fusion Transformers. This system significantly enhanced the detection of cyber threats and anomalies in real-time.
Network Configuration Recommendation System (RecSys): Leveraging Deep Deterministic Policy Gradient (DDPG) for continuous action spaces, the team built a RecSys that optimized network traffic, leading to substantial efficiency improvements. This innovation was noteworthy enough to warrant a patent filing.
Data Generation with Deep Reinforcement Learning (DeepRL): To augment the training and testing datasets, DeepRL was employed as an adversarial component, generating high-quality, novel labeled data. This initiative not only expanded the dataset but also enhanced the robustness of their defense models, culminating in another patent filing.
Network Routing Optimization: Through the application of Deep RL and dynamic programming techniques, including DeepQ, the firm created algorithms that optimized network routing, resulting in significant performance enhancements.
Graph Neural Network (GNN) Utilization: The implementation of GNN enabled precise predictions at both node and link levels within the network, further refining the system’s efficiency and reliability.
Results
The firm’s AI-backed initiatives have transformed their cybersecurity and network management capabilities. The bespoke cyber defense system has drastically reduced vulnerability to cyber threats, while the AI-driven network optimization tools have significantly improved traffic efficiency and client satisfaction. The success of these initiatives has not only reinforced the firm’s reputation as a leader in cybersecurity consulting but also demonstrated the tangible benefits of AI in solving complex industry challenges.
Advancing Retail Innovation with AI at a Nationwide Retailer
A leading nationwide retailer embarked on an innovative journey, focusing on enhancing their data-driven strategies. The research and development efforts were spearheaded by a Senior leader, exploring state-of-the-art applications in data science to elevate the shopping experience and operational efficiency.
The retailer aimed to refine its forecasting accuracy and personalize the customer shopping experience. The need to integrate advanced predictive models for better stock management and to develop a dynamic product recommendation system that adapts to customer preferences in real-time was paramount. Additionally, enhancing the internal search engine to improve product discoverability and relevance was crucial.
The Solution
Forecasting Modeling Framework: The team employed State Space Models and Deep Deterministic Policy Gradient (DDPG) Reinforcement Learning to develop a robust forecasting model. This framework was designed to predict market trends and customer demand more accurately, facilitating smarter inventory management.
Dynamic Product Recommendation System (RecSys): Using deep reinforcement learning, a novel RecSys was created that dynamically adjusted to real-time customer interactions and preferences, providing personalized product recommendations and improving the overall shopping experience.
Internal Search Engine Enhancement: To improve the accuracy and relevance of search results, an advanced search engine was developed, combining Natural Language Processing (NLP) models, specifically BERT (Bidirectional Encoder Representations from Transformers), with traditional keyword-based search methods. This hybrid approach significantly improved the precision and efficiency of the internal search functionality.
Results
The implementation of these AI-driven solutions led to remarkable improvements in operational and customer service metrics. The forecasting model enhanced inventory management, reducing overstock and stockouts, thus saving costs and increasing revenue. The dynamic recommendation system boosted customer engagement and sales by delivering more personalized and relevant product suggestions. The enhanced search engine improved the ease and speed of product discovery, leading to better customer satisfaction and increased conversion rates.
YRZ Enterprises
Asset Metrics Hub
All enterprise asset management solutions are very complex and require special training and specialized expertise to setup and integrate into an organization. The existing solutions do not provide out of the box integrations with IoT data collection. Implementation time varied from 1-2 years.
The Solution
LoadSys developed an enterprise solution for physical asset management that has prebuilt data collection and maintenance models for various asset classes and developed a framework for connecting equipment monitoring sensors with abilities to process thousands of data points per second. The intelligent data processing was architected to draw actionable insights and automated maintenance procedures. The expected implementation timeline is cut to 3 months.
Technologies
AWS SAM, AWS Lamba, AWS S3, AWS RDS, AWS Kinesis, AWS SNS/SQS, MQTT, AWS Athena, AWS Redshift, AWS Quicksight, AWS CloudSearch, NodeJS, ReactJS, React Native, TypeORM, React MUI, ML/AI for predictive analytics
Centralized Pay System Across Multiple Department Units for a major University
A leading University has many departments within the University. These departs include Technology, Engineering, Education, HR, Admissions, etc. Just to name a few. The University’s accounting for each department is a separate logical unit. Each department does financial transactions which involves receiving payments that originally went through the University and had to manually be recorded based on what department the transaction pertained to.
The Solution
LoadSys developed an ePay platform that also integrates with the University’s SSO (single sign on) platform so that users can authenticate with their existing university logins. The platform allows departments to receive payment and in turn the finances are logically separated by department.
Technologies
A07 Online
Platform for selling used wedding dresses and accessories
While LoadSys built the original platform for POWD, it was limited to collecting listing fees only. A07 had the vision to create a fully custom seller system where seller’s could manage their listings, but the front-end e-commerce portion would be handled by Shopify, a hosted e-commerce solution. In addition, they wanted to be able to collect a percentage of the sale of the dress and not just a listing fee. Unfortunately the old system would not make that change easy.
The Solution
Technologies
Searing Industries
Product QA/specs data capture
Searing manufactures steel tube and pipe. The product is sent to customers with spec sheets. The problem is that too many customers were losing these sheets and would call Searing requesting either a new sheet or the data, which was a manual process.
The Solution
Technologies
All Star Delivery, Inc
Warehousing and Logistics Platform
All Star was taking on new, larger clients that were very demanding and had a large number of food products and brands that they were warehousing. The current software platform they were using was simplistic and manual. Products were entered manually by employees. With 10s of thousands of products across hundreds of brands being entered, this was just not physically possible to maintain.
The Solution
Technologies
Engage
Multiple Ongoing Software Projects
Engage is a custom software development company that takes on some large and exciting projects, typically in the government sector. Often times they need resources quickly where hiring a new developer or project manager is not cost effective.
The Solution
LoadSys and Engage have been in a strategic partnership since 2007. Currently we support and manage around 7 projects for Engage providing ongoing support and new development for their clients. Having a trusting partner, Engage considers our relationship a big win for them and their clients.
Technologies
Laravel, WordPress, WP Engine, Salesforce, Fonteva