Scale your business with Artificial Intelligence

There are many applications for Artificial Intelligence (AI) for business, including Generative AI (GenAI). We design systems that perform tasks that typically require human intelligence, including reasoning, learning, and problem-solving across various applications. Leverage AI to free up time for your employees to focus on strategic roles.

What is the difference between AI and GenAI?

The difference between GenAI and AI lies primarily in their functions and outputs. AI broadly refers to computer systems designed to perform tasks that typically require human intelligence, including reasoning, learning, and problem-solving across various applications. 

In contrast, GenAI specifically refers to AI subfields that create new content or data, such as text, images, music, or code, based on previously observed data. Thus, while all GenAI is a form of AI, not all AI systems are generative. AI and GenAI offer a wide range of applications for businesses, often complementing each other in different operational, strategic, and creative capacities.

Benefits of artificial intelligence

Fully automate business processes

When AI applications are combined with RPA tools - full automation of any business users’ need is possible. This frees up time for your employees to focus on the profit-driven tasks.

24/7 Customer care

Not only does AI allow you to make faster and more accurate decisions, but it brings you closer to your customer’s preferences and allows you to improve your customer’s experience. With a bot’s ability to use past data to recommend quick solutions to users, the impact of AI on customer service can be significant.

Data-predictions can be made

Gather data-driven insights enabling you to make strategic judgements and take action. For example, in sales forecasting and candidate screening.

What artificial intelligence can do for your business

Artificial Intelligence (or AI) technology has become increasingly advanced with a range of applications. For a business looking into AI, a key area of interest is Machine Learning. Machine Learning is a type of AI application that learns from data and becomes increasingly precise over time. As a result, Machine Learning is the perfect partner for RPA. Where RPA tackles structured data, AI solutions are able to manage, and make sense of, large amounts of unstructured data.

Another application is Conversational Process Automation supported by Conversational AI. Conversational Process Automation is the automation of customer-facing tasks via chatbot interactions, where most of the time, the chatbot is integrated with core systems enabling end-to-end processing. Building on this, Conversational AI is an additional complex layer that makes machines capable of understanding, processing and responding to human language.

Applications for AI in Business:


Operational efficiency: AI systems can optimise supply chains, predict maintenance needs, and automate routine tasks.


Customer insights and analytics: AI helps in analysing customer behaviour, predicting trends, and providing insights that guide marketing and product development.


Decision support systems: AI can assist in high-level decision-making by providing real-time data analysis, risk assessment, and scenario simulation.

Top 3 Use Cases for AI in Business:

Automated customer service: AI-powered virtual assistants can handle customer inquiries, support tickets, and live interactions, improving response times and customer satisfaction.

Human resources and recruitment: AI can streamline the recruitment process by sorting through applications, matching candidates with job descriptions, and predicting candidate success.

Email automation: AI can streamline the process of extracting information from emails through several automated steps. The contents are identified, categorised and fed into a subsequent automation process. The result? Enhancing efficiency and accuracy in data handling and workflow management.

Boost RPA solutions with artificial intelligence

Artificial Intelligence in hyperautomation

When we pair AI with RPA both structured and unstructured data can be automated. Data powers Machine Learning and our software robots love data – the more data they receive, the better the decisions they can make.

With our expertise in Natural Language Processing (NLP) and Document AI Solutions we enable you to optimally utilise your data. As a result, your efficiency and customer experience are significantly improved.

AI implementation process

At Ciphix, we streamline your business with our AI implementation process, ensuring you stay ahead in a data-driven world. This process is divided into 3 phases:


Phase 1: Data Collection & Understanding 
We begin with a comprehensive understanding of your business needs to guide our data collection, ensuring the AI solutions we develop are tailored to your objectives.
Our team prepares and analyses the data, uncovering insights through exploratory data analysis to inform our AI models.


Phase 2: Model Building
We craft and evaluate bespoke AI models, focusing on accuracy and reliability to meet your business goals.


Phase 3: Deployment
The AI model is seamlessly integrated into your business, with continuous improvements to align with evolving objectives.

Our implementation partners

To build and implement AI solutions we use several software tools. Our toolkit includes AI resources from Microsoft Azure, Google and OpenAI to apply advanced AI algorithms and language models, and UiPath for streamlined document processing. We embrace the flexibility and power of major cloud platforms like Microsoft Azure, Google Cloud and AWS, ensuring our solutions are not only hosted on secure, high-performance infrastructures but also benefit from the extensive AI resources these platforms offer. By deploying our solutions through these cloud services, we guarantee scalability and seamless integration, allowing your business to innovate rapidly and efficiently.

Frequently asked questions about Artificial Intelligence

Artificial Intelligence (or AI) is a type of computer science which enables smart machines to handle tasks that usually require human intelligence. Despite its artificial nature, the mission behind AI is to further human advancements; within the field of business particularly, AI can prove extremely beneficial and it has, so far, been responsible for major transformations globally.

AI takes large amounts of data and applies an intelligent algorithm in order to pick up on patterns and gear solutions towards perception and thinking type behaviors as well as action. AI can be powered by deep learning, machine learning or another, simpler set of rules. Artificial Intelligence is able to mimic human intelligence providing decision making solutions. Artificial intelligence solutions can also be layered with cloud computing to enable businesses to manage insights from a large volume of data, to optimize workflow and more. AI is also used to boost cloud computing services in a number of ways.

There are several reasons why AI might be used in business. The capacity of artificial intelligence to work with huge amounts of data makes it ideal for sales forecasting, employee candidate screening and more. Along with the way in which it compliments Robotic Process Automation, AI can work alongside other technologies to boost functionality. Conversational software, like Siri for example, could not exist without artificial intelligence.

Deep learning is an artificial intelligence function that imitates the human brain in its ability to process data, spot patterns and make decisions. Deep learning intelligence continues to get “smarter” based on the more data it has to work with and, as a result, has a wide variety of real world applications. One only has to look at the effects of deep learning on trading within financial services to see an example of how it can revolutionize an industry.

The future of artificial intelligence is a much talked about topic. As artificial intelligence becomes even more intelligent, experts predict that our interactions with it will be more frequent and more complex. For example, artificial intelligence will be able to work alongside humans to solve problems in real time. Experts also predict that AI and cloud computing will merge in order to provide a more holistic system, allowing businesses to streamline their AI projects and achieve even greater things! The one thing that is clear, above all else, is that artificial intelligence is not going away. Businesses that adopt AI solutions find themselves in a great position to tackle the challenges of the 21st Century.

Want to know how intelligent automation can help your business?

Golden Rules for your Hyperautomation Journey

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