Where BRAINSTORMS translate into BUSINESS APPLICATIONS

We explore the veins of AI to obtain the right tools to set your ideas in motion.
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1. Machine Learning

We take your business several notches higher with customised machine learning solutions.

Observation and Analysis: Of client’s preferences and style.

Recognition: Of a specific pattern and inconsistencies.

Prediction: Of outcomes based on known data.

We offer advanced algorithms to resolve key business challenges, facilitating data-driven decision making and creating innovative business models. We create future-ready ML-driven applications by using techniques like pattern recognition, computational intelligence, nature-inspired algorithms and mathematical optimization.

Areas of our expertise:

  • Clustering
  • Anomaly Detection
  • Time Series Forecasting
  • Recommender Systems
  • Digital Signal Processing
  • Artificial Neural Networks

2. Deep Learning

GPU-accelerated deep learning solutions by our experts allow clients to discover new ideas and processes, as well as adapt to mercurial business scenarios. We pledge to provide deep learning services that promote superior business models, improvised products and advanced services.

Deep learning is a type of machine learning based on artificial neural networks, which means algorithms inspired by the human brain, in which multiple layers of processing are used to extract progressively higher level features from data. Deep learning is part of a broader family of machine learning methods based on artificial neural networks with representation learning

Deep learning is a type of machine learning based on artificial neural networks, which means algorithms inspired by the human brain, in which multiple layers of processing are used to extract progressively higher level features from data. Deep learning is part of a broader family of machine learning methods based on artificial neural networks with representation learning

Construct cognitive frameworks

Recreate human responses

3. Natural Language Processing (NLP)

NLP taking communication beyond words. We have progressed to the extent that our systems are equipped to fathom underlying emotions from expressions, utterances and behaviors.

(A)
Extraction of data from texts and speech
(B)
Generate comprehensive texts

Identification of human emotions and context.

We facilitate the labeling, creation, and validation of domain-specific text data in a broad variety of languages.

Sentiment Analysis

NLP based models can understand and infer the right context and undertone to gauge consumer needs from their complexities. Sentiment Analysis is an opinion mining technique that can be proactively used to formulate business strategies, exceed customer expectations, generate leads, build marketing campaigns and open up new avenues for growth.Our effort includes taking a stride beyond simplistic sentiments and analyzing the logic behind the positive and the negative.

Named Entity Recognition

Named-entity recognition is a subtask of information extraction that seeks to locate and classify named entities mentioned in unstructured text into pre-defined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc.

Intent Classification

We analyze customer conversations and train the model to compute sentence vectors and classify text input into various datasets. This automates the process of understanding sophisticated linguistic nuances as well as helps in identifying user intent, undertone and objectives

Utterance Collection

Leverage the benefits of a network of fluent annotators with free text utterance collection jobs to gather text strings based on scenarios or prompts to drive your conversational agents. Our platform employs workflows and quality controls and supports multiple languages to ensure the highest quality free-text utterances.Leverage the benefits of a network of fluent annotators with free text utterance collection jobs to gather text strings based on scenarios or prompts to drive your conversational agents. Our platform employs workflows and quality controls and supports multiple languages to ensure the highest quality free-text utterances.

Optical Character Recognition and Transcription

Several renowned global companies avail optical character recognition (OCR) models from us. The solution provided by us brings higher accuracy to your algorithms which makes tasks such as identifying specific areas of text in PDFs with bounding boxes, transcribing relevant sections of PDFs, or validating model outputs, easy.

Information Extraction for NLP

Information extraction is the task of automatically extracting structured information from unstructured and/or semi-structured machine-readable documents and other electronically represented sources. Tasks as simple as classifying sections or whole documents, or copy/paste functionality to something more complex as identifying important strings of text crucial for your NLP models fall within the purview of our platform.

Relevance Scoring

Relevance score is calculated based on the positive and negative feedback we expect an ad to receive from its target audience. The more positive interactions we expect an ad to receive, the higher the ad's relevance score will be.

Text Categorization

Automated text categorization helps categorical listing of critical business data and segregate them for ease of search and organization. By classifying text in this manner, automation allows you to minimize errors, scale real-time insights, save time, and extract the most value out of available information. Reduce inconsistencies and manage your documentation at a fraction of the cost!

4. Predictive Analysis

Predictive analytics borders on a variety of statistical techniques from data mining, predictive modelling, and machine learning, that analyze current and historical facts to make predictions about future or otherwise unknown events.
Historical data are fed into the predictive algorithms prepared from predictive analytics (mentioned above) and a model derived out of it. Further, new data are fed into the model to derive the predictions. Predictive analytics based on statistical algorithms, data, and ML to determine the possibility of future outcomes.

(A) Prediction of business-related trends and actions

(B) Identification of business-critical risks

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