Natural language understanding, intent detection, topic modeling, theme extraction, sentiment analysis

Face recognition, biodiversity species classification, object detection

Density based counting architectures

Speaker diarization, voice clustering, emotion & gender detection

AI-driven Legal Document Analyzer

Identify voices with AI. This Deep-learning empowered application recogizes Gender and Emotions in an audio file. Try it out.

Using this API you can count any number of objects in the crowd. The application ML-driven and generates heatmaps for the crowd extracting an exact count of objects in the crowd.

Which words were used most during corporate earnings calls? How has this changed over time? Gramener's text analysis shows patterns in text

When a caller calls a call center, or enters a phone conversation, deep learning techniques can help identify and verify the person. This is useful in transcribing recordings of panel discussions too.

Active learning, seeks to select the most informative data points, with the objective of reaching a performance comparable to that of passive supervised learning algorithms, using fewer training instances.

What's your gender? How old are you? Are you angry or happy? The face recognition app tells it all.