Machine learning hero Miran

Machine learning

Go beyond human vision and transform your data into valuable input with intelligent machine learning services.

We develop machine learning applications that make successful outcomes.

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Make your data work for you

Employ AI practices to craft and implement machine learning algorithms that will induce your digital transformation.

Our team will define possible machine learning applications to optimize the processes of your organization. Whether your goal is to improve the quality of your customer service, manage your resources efficiently, speed up the work pace, improve the accuracy of your operations, estimate the execution time, or make all the right business choices, we will create the fitting strategy frame.

A computer program's ability to extract knowledge from data enables us to apply the right tools and integrate appropriate algorithms to transform data into a business advantage.

Adaptation

Improvement

Automation

High-performance algorithms for a productivity boost

Machine learning

Natural language processing (NLP)

We will build algorithms that create a representation of language in a form that is understandable by machines. This will convert your data into innovative and intelligent applications tailored to your business requirements.

Computer vision

Extract information from digital assets and use it to perform actions or use anomaly detection to eliminate faulty items from production. Training computers to understand the visual world can help you enhance the customer experience, reduce costs, and increase security.

Data analysis

Customer analytics

Customer analysis allows finding the sweet spots that will drive loyalty and sustainable growth. By capturing day-to-day customers' behavior, you can enhance their overall experience, understand how they use your products and services and proactively engage with them.

Predictive analytics

Extract information from current and historical data to determine if those patterns are likely to emerge again. This way, you'll allow your business to adjust where to use your resources to take advantage of possible future events, reduce risk and identify opportunities.

Time series forecasting

We will analyze time-series data measured in chronological order, apply a forecasting algorithm, and derive a forecast. This will give you a hand with predicting the target variable's future values and identifying seasonal trends as well as upcoming trends.

Building data pipelines

A data pipeline uses a set of actions to automate the process of moving interpreted raw data from several sources to a targeted location for analysis or virtualization. Building a data pipeline results in a smooth flow of information and your ability to gain a competitive advantage.

Reviewing data architecture

During our data architecture review, we analyze every aspect of your process to ensure that data management meets business needs, is optimized, and handled appropriately. Following our recommendations will bring your system to a healthy state and maximize its full potential.

Machine learning models that produce real results

We devote great attention to planning to ensure positive outcomes of systems based on machine learning. If they are not working properly, there could be some negative consequences, which depend on the nature of the task at hand. Therefore, having a risk-averse mindset, we understand how important it is to design these systems carefully and with dedication.

ML requires continuous research, especially in building model architectures, as new findings occur almost daily. This is why high-quality analysis is something we put an emphasis on throughout the process. We are determined to build custom AI models for our clients to help them benefit from their valuable data, strengthen internal operations and make their business less vulnerable in the future.

From raw data to fully developed model

01

Data analysis

First, we will analyze your data and the KPIs you want to accomplish - based on the findings, we will define the type of task we need to put in motion.

02

System and model architecture

The system should be carefully and correctly designed to handle all capabilities of the task and the model architecture should be built with the aim to solve efficiently the desired goal.

03

Testing

Ensuring that the software system works according to the requirements is crucial and that it points out all the defects and flaws during development. This includes testing the model performance in real-time data.

04

Delivery

After all previous steps are successfully done, the last step is releasing an efficient, reliable, and, most importantly, effective system to the production.