Machine learning is hot topic today and our constant research and innovation in this area enable us to tackle demanding challenges in development of self learning systems.
Business process automation using intelligent systems is crucial for maximizing business efficiency. This is essential for staying competitive in the continually evolving global economy. As a fundamental part of this effort, machine learning has become an imperative asset in increasing the value of a product or a service. Its use of statistical models and algorithms for data prediction, and classification pushes the frontiers of possible solutions far beyond classical computer programming and into the artificial intelligence (AI) arena.
Artificial intelligence and machine learning have already altered the way companies conduct their operations. The majority claim to have implemented the technology in significant processes such as marketing and sales, supply chain management, customer support, and cybersecurity.
Business benefits of machine learning
Making the right decision at the right time can be crucial for business success. But without technology capabilities, it would be impossible to extract the correct data and integrate it into everyday business. With machine learning, a company can quickly transform an extensive data set into specific knowledge and use it to make proactive measures and stay on top of their competition.
Cyber-security threats, security breaches, and anomalies frequently occur in real-time, with little prior warning. Any unusual networking actions must be recognized promptly before the intrusion escalates into a full-fledged security breach, information leakage, and service outages for businesses to maintain network security. Machine learning algorithms assist in anomaly detection in network behavior.
While large companies dominate the market share, numerous businesses pursue competitive advantage in other areas to maintain profitability. In small and medium-sized companies, that advantage is usually provided by innovative technologies, services, and business models.
What to consider before implementing machine learning?
The first step is to determine what your company needs. What challenges do you want machine learning to solve?
The second part is data - do you have enough quality data for machine learning algorithms?
Last but not least – internal capabilities. To gain business benefits from machine learning, you should have a team of qualified experts.
How can business grow through machine learning technology?
- Business process automation
- State-of-the-art data analytics
- Real-time intelligence
- Identifying bottlenecks
- Advanced data classification
- Transforming data into knowledge and actionable intelligence
- Easy spam/fraud/event detection
Our approach to AI/ML projects
- Gathering, processing, and analysing data required for machine learning processes
- Development and evaluation of models and learning procedures for a specific task
- Testing on relevant public and private benchmark datasets
- Building an app around our models and a Proof of Concept
- Production deployment and Performance monitoring
What's in it for you?
Depending on your business needs, you can choose between several different cooperation models.
Case studies
Tire Recognition Meets Machine Learning
Our client is a huge wholesale of tires and distribution center, a B2B business that has deals with many smaller shops that buy and resell their tires. Find out how machine learning and computer vision helped their business growth.
RedAI
The RedAI app is an artificial intelligence software solution that enables FMCG/CPG companies in Retail and HoReCa to detect, classify and control their own and their competition’s SKUs (products) with a series of photos taken from a mobile device or tablet.
This semi-custom application provides full automation of the in-store execution process. It generates real-time results and delivers complete business intelligence reports. The main purpose of RedAI is to perform visual perception and brand recognition.
There are many reasons why companies integrate machine learning into their fundamental activities. Enhancing consumer segmentation and targeting and eventually raising a company's revenue, growth, and market position are just some of them.
