Technology Used

We worked on lots of models & objects/data for training. We will now present you our current achievements and ongoings.


Machine Learning (ML)

For analyzing large data-set we use machine learning algorithm, which is very robust and astonishing in it's effect.

Natural Language Proccessing(NLP)

To process the input text from STT (speech to text) we use natural language processing.


Our Own Algorithm

For text classification and predicting response our team build a algorithm which try to make THEiA a super-bot.

Speach Recognition(STT & TTS)

We receive speech from user as input, STT convert it to text and then THEiA predict a text response. we convert text to speech by TTS.

Process Image

The Process THEiA Folllows

01. Machine Learning

  • - Utilize Apache SparkML
  • - Use JAVA wrapper for Android
  • - Initial data inventory for Machine Learning

02. App (Android & ioS)

  • - Android app for frontend functionality/user engagement with ML
  • - Android connects with Python/Django backend

03. The AI Part

  • - Grow data inventory based on conversation & user input
  • - Unsupervised model for auto learning from input