
Explainable AI
Build trust with human interpretable explanations of ML/Deep Learning models based on the patterns found by the model in data. Explain your black box models from local interpretations to global understanding using various explainability techniques best suited for the problem at hand.
ML Deployment
We build and automate your end to end ML Pipeline with
model building, training and inference jobs deployed on your
choice of (Cloud) Platform.


Anomaly Detection
Detect anomalies in an entity’s behavior that differs from the usual patterns which majorly translates to some kind of a problem like a credit card fraud, failing machine in a server, a cyber attack, etc.
Natural Language Processing / Multimodal Sentiment Analysis
Analyze context, relationships, entities and emotion to derive better meaning from text and speech. Analyze sentiments not just from text, but also from audio. Built multimodal models that draw context from text and tonality using spectrograms. The sentiments drawn from multimodal models are much more reliable and wholesome as opposed to just text sentiments.


Projection/Prediction
Build accurate prediction models using various Machine Learning / Deep Learning techniques. Predict future outcomes for business use cases like Lead Conversion, User Churn, Revenue Forecasting etc.
Recommendation Engines
Suggest products, services, information to users based on analysis of historical data and behavior of similar users using approaches like Collaborative/Content based Filtering and knowledge based systems.


Cohort Analysis
Use Behavioral Analytics to group customers based on shared traits which help you understand your customers better and make informed product/marketing decisions. Use this analysis to identify your next Campaign’s Target Audience/ Channel/ Content for best performance/metrics.
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