Think, Transform & thrive to change (AI)

Artificial Intelligence (AI) has evolved and changing today's world. It is the simulation of natural knowledge in devices that are programmed to learn and imitate the activities of humans. At COGNXT, we have innovative ways to implement AI, analytics, automation, and data that improve people and process both.

Our team of professionals works with you to contribute the appropriate solutions and services to achieve your business objectives quicker, manage data and AI implementation, thus delivering continuous innovation and growth.

Our AI Capabilities

Predictive Analysis

We use different data mining, predictive modeling, and analytical techniques to bring together the management, information technology, and modeling business process to make predictions and to classify risks and opportunities for the future. 

Machine learning

With the help of machine learning, our data scientists enable computers to learn from data. This technique yields outcomes that function well without explicit programming of rules. Data science and machine learning are popular intelligence elements of today. 

NLP and Text Analysis

We can enable your existing systems to interface more conveniently with speech recognition capabilities; and go beyond conventional reporting to more intuitive interactions.

Computer Vision

In addition to adorning systems with speech capabilities, we take the machine and human interface to the next level of visual recognition too. We help businesses derive meaningful insights from visual-media inputs, for instance – identifying facial identities, expressions, or objects in a real-time visual scene.

Sentiment Driven Inferencing

Our Artificial Intelligence teams continuously strive to take computer and human interactions to the next level. We can conduct sentiment analysis on real-time data streams, like social platform posts, to extract trends and insights on market behavior based on the same.  

Process Optimization and Automation

We partner with enterprises and help them streamline a business process by reducing complexity by identifying optimization avenues and implement automation points, which eventually enhance service excellence, reduce errors, promote service delivery and significantly reduce operational cost. 

Steps
ARTIFICIAL INTELLIGENCE IMPLEMENTATION

Artificial Intelligence (AI) performs a principal role in promoting productivity, efficiency, and clarity across industry segments and domains. At COGNXT, we implement a proven strategy and framework that transform enterprises and help them reap the benefits of machine-driven intelligence.

Data preparation is the most crucial step in the AI workflow. Without sound and accurate data as input to train a model, projects are more prone to fail. Training of an AI model starts with the process of precisely tagging data from various data sources. Our implementation experts focus on classifying input datasets, pre-processing data elements, and assuring correct tagging of the data as per the preferred model. 

Once the data is cleansed and accurately tagged, we model the intelligence workflow and use the classified datasets to train the AI model. A well-planned modeling phase goes a long way in building a robust and reliable model that can deliver meaningful information based on the data. 

Simulation and testing for accuracy are crucial elements that validate the accuracy of an AI model. Ensuring everything works well together, with other systems, before deploying a model into the real world. Before deployment, we reassure that the model will respond the way it is supposed to, no matter the situation.  

Deployment is the last stage in the AI life cycle and can get clumsy with inexperienced hands. Through the deployment phase, our architects and data engineers work in tandem and progress the AI model through various deployment environments; while also ensuring that the model consistently delivers sensible business decisions based on data.

Industries Catered

Manufacturing

AI is implemented in the manufacturing sector to extract data, recognize patterns, study, and adapt to new situations through machine intelligence, learning, and speech recognition. Using AI, manufacturers will be able to build fast, data-determined decisions. Promote enhanced production results. 

Healthcare

AI in healthcare involves NLP applications that can learn and analyze clinical documentation, giving insight into understanding quality, developing methods, and better outcomes for patients, and also promotes forecasts based on the data and suggestions. 

Banking

 Artificial Intelligence is the future of banking with the prospect of advanced data analytics to combat fraudulent transactions and improve compliance; Thus assisting the banks with identifying frauds, discovering money laundering patterns, and suggesting product portfolios to enhance customer experience. 

Finance

 In the financial sector, one of the classical use cases for AI is to continually monitor cash accounts, credit accounts, and investment accounts to analyze a client's financial health, keeping up with real-time events and insights, eventually producing wealth management recommendations based on new incoming data.

Supply chain and logistics

By implementing AI in supply chain and logistics, one can improve the outcomes by predicting building-up bottlenecks, unexpected irregularities, and answers to streamline production scheduling that otherwise tends to be highly unsteady.

Retail

AI in retail includes machine learning, and deep learning is a key to generate insights like customer experiences, opportunities to increase revenue, rapid modernization, and reliable operations that differentiate you from your competitors.

Make your business AI enabled