Anomaly Detection & Hypothesis Generation

AI/ML solution that helps businesses spot patterns, surface anomalies, and create proactive alerts and resolution.

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Anomaly Detection & Hypothesis Generation
Accelerator Synopsis

Anomaly Detection & Hypothesis Generation aims to identify opportunities to improve and adapt to any anomalies within a specific time. Anomaly Detection & Hypothesis Generation built on state-of-the-art, proprietary AI/ML algorithms uses cloud resources to scale up anomaly detection on Big Data.


The users can create and update analytical datasets, toolkits, identify anomalies, and even create human-readable statistical explanations and hypotheses to take corrective actions.

Value Addition

Statistical Explanation

Our proprietary algorithms developed in-house can detect anomalies on a broader range of data sets and provide statistical explanations about why data points are classified as anomalies.

Hypothesis Generation

Using cutting-edge algorithms, the accelerator can identify anomalies and generate hypotheses based on other variables in the data to explain the anomalies.


Datasets & Connections

Users can connect to multiple data sources, update existing connections, and upload files directly into the application. Users can choose to run the algorithms on all or a subset of their data.

Anomaly Detection

A summary page that highlights anomalies and takes user feedback into account. Further, the deep-dive option provides statistical explanations and redirects to the generation of hypotheses.

Hypothesis Generation

A single landing summary page. It highlights the hypotheses for all the anomalies and tags them as a priority for the user to look into.

Summary of Results

A landing page containing a summary of model results and critical insights from the past week and some high-level KPIs and data health indicators customized according to business needs.


The application is based on a cloud framework and can be quickly scaled to support Big Data processing.

We use proprietary AI/ML algorithms to provide a more accurate output, human-readable statistical interpretations, and simple hypotheses.

Yes, the advantage of this algorithm is that it can efficiently run on different types of data.

Yes, we can incorporate customizations on the need basis. Every customer will have different UI and dashboard.