Technology companies

AI Solutions for Technology and IT Industries

Artificial Intelligence modules enhance the possibilities of any given software, regardless of the industry where it has been used. With AI onboard, software companies developing IoT, eCommerce systems, streaming platforms, or any online services can add the “wisdom” from data analysis to their products. 

The AI potential doesn’t limit to one particular area; on the contrary – it can be used in almost every sector as data are entirely “sector-agnostic.” Whether we are analyzing natural language, visual objects in the real-world, numeric data, and so on, AI may find a utilization. So, any software such as ERM, CRM, AI platform, or service with implemented AI models can be smarter.

AI-models features

Regardless of its purpose, end-users, and complexity, any software uses data and - as such - can be enhanced or scaled by harnessing AI models to analyze them quickly and more efficiently.

Data Platforms

Data engineering, which uses advanced methods of designing and building systems to collect and analyze raw data from multiple sources and formats, is essential for empowering any existing software.

Business benefits


Enhanced Customer Experience

AI-powered solutions help businesses to keep up with their customers’ needs, respond to their queries and grievances quickly, and address the issues more efficiently with – for example – chatbots using Natural Language Processing technology. But that is not all.

AI-based solutions can suggest much more personalized product offerings and embrace up- and cross-selling activities in retail. AI and IoT help optimize product placement in-store and run more effective ad campaigns. AI drives predictive analysis that can prevent inventory shortages.

Predictive analysis

AI algorithms can detect patterns in vast volumes of data and “translate” them into meaningful business insights. Advanced AI algorithms can predict what a particular customer is likely to buy, which can be an excellent foundation for personalized ad campaigns.

Moreover, AI can identify credit fraud in real-time, detect insurance claims fraud, set up dynamic prices based on the credibility of customers and/or potential problems with their liquidity, and so on.

Our challenges and how
we solved them

Reducing Manual Labor
Effective Usage of Data

Analyzing the increasing amount of constantly coming data in real-time has become a pain point for most businesses regarding internal and external operations. Support staff doesn’t have the capabilities to handle the sheer number of inquiries and daily problems, not to mention that manual processes are typically sensitive to errors.

With AI onboard, it is simply easier. Machine learning algorithms enable companies to automate routine tasks, freeing their employees to manage more high-level tasks or supervise the entire process.

Overwhelming amount of data

Technology companies – regardless if they offer services or develop products – struggle with effective usage of data coming from multiple sources.

Data is a direct way to improve the quality of their offering but the amount of it is typically overwhelming and hard to transform into meaningless business insights. With AI, the processes can be automated, data – fully embraced, and insights more accurate.


Business Process Automation
Data Engineering and Science
Image Recognition

Use data to enhance the business processes

One of the most general solutions driven by Artificial Intelligence is process automation. As “data is the new oil,” tech companies are constantly looking for ways to organize and use data to enhance the business processes across industries.

Automated processes decrease errors and time to value, boost the speed of delivery, upgrade quality, cut costs, and simplify the entire workflow throughout organizations. These benefits go beyond specific industries, and today’s tech companies aim to develop the patterns and solutions in line with the unique business needs of given companies.

Machine and Deep Learning can be harnessed to perform much more efficient data analysis. With the support of these intelligent technologies, organizations can create algorithms to process data (no matter what kind), build predictive models, and understand the potential impact of different trends and occurring circumstances upfront.

One of the most promising parts of AI development

Image recognition based on artificial intelligence recently came into stardom as one of the most promising parts of AI development. Often equated with computer vision (computer vision is a slightly broader term), image recognition is an area focused on learning computers how to interpret visual objects in the real world correctly.

In short, it is about making computers detect the differences between things in the real world and classify them into proper categories. Image recognition has recently evolved at a breakneck pace based on deep learning. We can observe the evolution in Visual and Voice search, where Big Techies – such as Google, Pinterest, and Amazon – are racing. But that is the end of possibilities gained by image recognition solutions.

Image recognition is also a crucial part of business automotive, finance, commerce, and healthcare.

Customer stories

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