ClaySys tries to stay ahead in the world of technology by gaining knowledge of cutting-edge technologies and delivering them as a service to our clients.
Artificial Intelligence, even in its early stages has huge potential to transform a business in many ways. Most businesses won’t be able to have an in-house team for developing and implementing Artificial Intelligence-based solutions in their company. This is where AI as a service gains relevance.
ClaySys has been at the forefront of Robotic Process Automation for many years and now has begun offering Artificial Intelligence as a service, which allows businesses to hire one of our Artificial Intelligence experts for consulting, development and implementation of custom AI-based solutions in your organization.
Since AI is based on training a system with existing data so that it can make predictions on possible outcomes, the financial sector has a lot to gain from artificial intelligence. An AI can go through enormous data dump to come up with outputs that are usually humanly done, such as evaluating a person’s credit score to decide whether or not to provide him a loan or a credit card.
Real estate industry requires a lot of personalization for a sale to happen. If a buyer doesn’t get what they were looking for, they will move on. Integrating AI into an existing dataset can help realtors convert prospects into customers by using effective data analysis, chatbots that can interact with customers, and by making relevant actionable recommendations.
Customer service platforms have had a lot of growth in recent years. Companies give much more importance to customer service than they did before. Artificial Intelligence can enable businesses to better serve their customers by automating customer interactions. Software that can respond to unique customer inquiries is the future is customer support systems.
Staying competitive by having a better understanding of the trends and gaining insights.
Artificial Intelligence allows companies to check on the historical buying patterns of their customers and make reasonable decisions based on it. It is based on these assumptions that they release promotional offers, discounts and coupons.
Business can deliver superior customer experience by utilizing AI-based analysis of what they would be needing in the near future.
With unprecedented data in their hands, a marketer or developer can make use of the social value metrics and incorporate the funnel analytics method to influence influencers.
Artificial Intelligence can deliver a personalized customer experience. It helps companies identify customers who have the highest propensity to buy.
AI allows you to search, retrieve information and make the best use of all the business data.
AI can analyze all the structured (geographic and demographic data) and unstructured (customer inputs from social media) data and forecast customer expectations.
This will help them strategize a plan and focus on both the urgent aspects of the business and the ones that may not seem so urgent now, but will eventually turn important in the future.
Artificial Intelligence can identify the reasons for a customer’s exit and model out others who are planning to leave. If you know this beforehand, you can plan strategies that would help you retain them. With predictive analytics, the advantage is that you can focus on relationship-building.
We are focusing on transformative technologies like computer vision and predictive analysis using machine learning that will create the next quantum gain in customer experience and unit economics of businesses.
Applications of Computer vision are face detection, object detection, and tracking, object recognition. For Computer vision, we use tools like OpenCV, Dlib, and Convolutional Neural Networks.
OpenCV (Open Source Computer Vision Library) and Dlib are open source computer vision and machine learning software library, which was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products.
Convolutional neural network (CNN, or ConvNet) is a class of deep, feed-forward artificial neural networks, most commonly applied to analyzing visual imagery. CNNs, like neural networks, are made up of neurons with learnable weights and biases.
Other Machine learning frameworks used are Scikit-learn, Tensorflow, and Keras.
Scikit-learn provides a range of supervised and unsupervised learning algorithms via a consistent interface in Python. This stack includes:
Keras is a high-level neural network API, written in Python and capable of running on top of TensorFlow. Keras allows easy and fast prototyping (through user friendliness, modularity, and extensibility). It supports both convolutional networks and recurrent networks, as well as combinations of the two and runs seamlessly on CPU and GPU.
Artificial Intelligence being a relatively new technology raises a few eyebrows questioning its efficiency and reliability. ClaySys delivers a proof of concept for free. This demo will show you the specific details about how we plan to develop and implement the custom AI solution you require.
Ready to discuss your project? Get a FREE proof of concept now.
AI services don’t have to be expensive. ClaySys is one of the consultancy firms serving in the USA that provides affordable pricing plans for all development services.
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