Artificial Intelligence
& Machine Learning

Unlocking Tomorrow‘s Potential with
Today’s AI Solutions

At Infotrend, we excel in developing AI-driven solutions such as building recommendation systems that boost customer engagement by analyzing user behavior patterns, advanced anomaly detection algorithms that can identify and flag unusual patterns in your data, and natural language processing models that automate content categorization and sentiment analysis, saving valuable time and resources.

Natural Language Processing

We specialize in the cutting-edge field of Natural Language Processing (NLP), a branch of Artificial Intelligence that focuses on the interaction between computers and human language.
  • Through techniques like Topic Modeling, we identify patterns and themes in large volumes of text. This capability is crucial in extracting valuable insights from text data, aiding in decision-making processes, and enhancing information retrieval systems.

Anomaly & Outlier Detection

We leverage anomaly detection to identify rare items, events or observations which raise suspicions by differing significantly from the majority of the data set. We use outlier detection to identify data points that are considerably different or inconsistent with the rest of the data set.

  • By employing advanced algorithms and machine learning techniques, our approach ensures robust detection of these anomalies and outliers, providing our clients with reliable insights and the ability to preemptively address potential issues.

Supervised & Unsupervised Learning

We use Supervised Learning to rely on labeled datasets to train algorithms. In this approach, the model is ‘supervised’ as it learns from the provided input-output pairs, enabling it to make predictions or categorize data with high accuracy for new, unseen information. We use Unsupervised Learning to discover underlying patterns or structures within unlabeled datasets. This is particularly powerful for clustering and association tasks, where the algorithm discerns inherent groupings or relationships without any prior knowledge.

Time Series Analysis

We leverage time series analysis as a crucial tool in our data-driven decision-making process to discern patterns and predict future trends from historical data. This robust methodology not only enhances the accuracy of our forecasts but also allows us to conduct profound anomaly detection, ensuring our insights are both reliable and actionable.

Client Example

Infotrend harnessed the power of predictive and machine learning models to perform anomaly detection on an astonishing scale, analyzing billions of financial data records. Our statistical models, using Z-Scores, Modified Z-Scores, and Mahalanobis Distance, meticulously assessed each data point’s divergence from established norms. These models excelled in identifying anomalies that significantly deviated from expected patterns, even within massive datasets housing millions of records. They not only offered scalability but also an efficient means of uncovering irregularities, becoming an indispensable asset for our client’s data integrity, quality, and security. We seamlessly deployed our anomaly detection engine on the Amazon Web Services (AWS) cloud, harnessing SageMaker, S3, and Redshift to uphold ML Ops best practices. Additionally, we harnessed QuickSight dashboards to visualize potential anomalies, thereby deriving substantial value and insights from the data at hand.

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About Infotrend

We build technology solutions for federal agencies that address the challenges associated with big data, custom application development, emerging technologies and training. Our Agile, innovative approach and experience as a prime contractor managing a broad portfolio of government projects allow us to rapidly understand and solve the most complex issues in ways that reduce risk and increase efficiency.

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