Artificial Intelligence

Work with the most revolutionary technology the world has ever seen

AI is like an assistant with all your organization's knowledge. It processes and analyzes this information, offering innovative solutions.

Artificial intelligence_1

How can AI help you grow your business?

Artificial intelligence (AI) solves various industry problems, offering innovative solutions to complex challenges.

  • Increase revenue
    AI helps you analyze social media, automate ads, and make smart sales choices.
  • Ensure data security
    Machine learning detects fraud, such as credit card scams and identity theft. It saves companies money and protects customers.
  • Analyze large amounts of data
    Machine learning algorithms analyze data to predict trends. They help companies make decisions about product development and sales.
  • Improve process productivity
    Machine learning automates processes, saving time and costs. It predicts machine failures and recommends maintenance, avoiding downtime.
  • Improve customer satisfaction
    Predictive analytics finds customer trends and suggests products. AI chatbots speed up resolutions.
  • Optimize supply chains
    AI optimizes supply chains by predicting demand and managing inventory in real-time.

Our artificial intelligence (AI) capabilities

We provide consulting services and AI solutions to accelerate your business goals and enable sustainable growth.

Natural Language Processing

NLP solutions enable machines to understand and generate human-like language. Our NLP applications include chatbots, language translation, text content analysis, and sentiment analysis.

IoT and device automation

We innovate for companies through the use of IoT (Internet-Of-Things) in Industry 4.0 and the application of digital systems based on artificial intelligence.

Computer Vision

We help implement and integrate computer vision-based algorithms to train AI solutions and automate tasks such as voice recognition, image processing, object detection, and more – the way human visual systems can.

Predictive Analytics / Data Science

Utilizing Artificial intelligence, predictive analytics analyzes historical data to identify trends and make informed predictions about future performance. This capability is valuable for finance, healthcare, and manufacturing industries.

Generative AI

We use Generative AI systems to develop mathematical models and create different types of content, such as text, images, audio and synthetic data.

Chatbots

We understand the business need to offer dedicated 24/7 support, so we build chatbots based on artificial intelligence and integrate them into the client’s software – be it websites, mobile apps, etc.

Turn your AI concept into a reality

Implemented projects in

/ Projects we are proud of

Osoba wypełnia kartę związaną z ubezpieczeniem zdrowotnym

80% increase in detecting suspicious claims with ML algorithms

Industry:
Fintech
Technologies:
Python, R, Docker
Description:

Learn how we built ML models that would make it easier to check a high percentage of scams in the insurance industry.

Model:
Team Outsourcing
Duration:
4 months
Trzy kobiety wpisują kod pin do bankomatu.

DL model to limit customer loss for one of the largest banks in Europe

Industry:
Fintech
Technologies:
FastText, Keras, DyNET, Python
Description:
For the client, which is one of the five largest banks in Europe, we built a model to predict customer churn.
Model:
Team Outsourcing
ML in debt recovery

Operational efficiency of debt collection companies

Industry:
Fintech
Technologies:
R, Docker, Python
Description:

For one of the largest debt collection companies in Poland, we have developed ML models for the valuation and purchase of debt packages.

Model:
Team Outsourcing
Duration:
6 months
Quantup- ocena ryzyka

ML in automating the risk assessment process in the financial industry

Industry:
Fintech
Technologies:
R, Python, Docker
Description:

For a client dealing with the financial security of companies in the transportation industry, we built an ML model for assessing the reliability of end customers.

Model:
Team Outsourcing
Duration:
5 months
Application de la ML à l’optimisation de la consommation d’électricité

Utilizing Machine Learning (ML) in the optimization of energy use

Industry:
Energy
Technologies:
Python
Description:
For the client, a UKbased company providing solutions to optimize energy consumption, we designed a solution capable of building predictive models tailored to each institutional client.

AI Development Process – an iterative approach

When making a machine learning model, we go through many phases. They start with data collection and preparation. Then, we move to data training, evaluation, and continuous iteration.

This is a unique approach. It sets us apart from other companies because we repeat the cycle many times until we get good results.

We work closely with your team to create AI models and provide training for better understanding and efficiency.


I – Free consultation

The first step to understanding your problem is a free consultation, in which we first discuss your challenge and determine whether the implementation of an AI model would be effective and possible.  

II Workshop – Define your needs and AI strategy

The second step is to conduct workshops online or on-site at the customer’s premises. They usually last 1–2 days. We’ll identify your problem, your data, and how it affects your application or company. Then, we’ll determine when your AI model is good enough.

Only after the workshop can we decide whether the project is worth pursuing—and then comes the second offer.


III Project – Feasibility study
(POC)

The third step is the implementation of the PoC. And here we can differentiate between elements such as:

1. Data acquisition and preparation
During this stage, we help collect relevant data from various sources, organize it, and prepare it for use as training data.

2. Model development
We choose the right model for the problem and train it using a training dataset, identifying the most relevant variables.

3. Evaluation and refinement of the model
We evaluate the performance of a trained model using a separate data set (test/validation set) that it has not seen before. Typical evaluation metrics include accuracy, precision, and score.

VM.PL – Artificial Intelligence solutions provider 

What will you get working with us?

01
Interactive PoC for your AI software.
02
Data-driven predictions that instill confidence in high return on investment.
03
In-depth understanding of methodologies to avoid common mistakes and maximize the data.
04
Consulting and advising on alternative business opportunities, architecture, and technology.
05
Choosing the right approach for your needs. You can cut costs by combining classical stats with AI / ML / DL.

What are the risks of not applying AI correctly?

01
85% of AI projects will produce flawed results due to biases in the data, algorithms, or the teams responsible for managing them.
02
Only 53% of projects go from prototypes to production.
03
Only 15% of AI projects will be successful.

How will VM.PL help you overcome these challenges?

 

  • 95% of our AI projects are successful –achieving the set goals, on time and within budget.
  • the remaining 5%, we put a quick and reliable diagnosis possible for missed targets to avoid unnecessary costs.
  • 85% of projects go into production.

Let’s talk abut your AI
needs

Technologies we use in AI solutions

Logo Angular
Logo Vue.js
Logo MySQL
Logo React
python logo
Logo docker - 1
Android Logo

Industries we use Artificial Intelligence

Medicine

AI tools analyze medical images, patient data, and genetics. They help healthcare pros diagnose diseases more accurately and quickly.

Finance

AI algorithms analyze transactions. They find anomalies and signal fraud in real-time. This boosts financial system security.

Production

AI improves industry efficiency. For example, it uses predictive maintenance to prevent equipment failures. It also optimizes processes to cut waste and save energy.

Energy

AI helps energy companies forecast use and optimize production. It also assists with managing assets by improving maintenance and predicting failures.

E-commerce

Marketing and sales teams use artificial intelligence to better reach potential customers, optimize outreach campaigns and prioritize leads.

Telecommunication

AI supports network management, customer service, security, and resource optimization. This helps companies to work better and give higher quality to customers.

Meet our AI Experts

Artur Suchwałko

PhD

Arthur has 20+ years of experience in advanced analytics. He earned a math doctorate and did 100+ projects for companies at all stages-from startups to global corporations. 

Agnieszka Suchwałko

PhD

Agnieszka is a technical sciences doctor focused on AI projects. Solving real problems with modified ML algorithms is her job and passion.

Rafał Pisz

Rafal is a managing director and shareholder at IT companies DATAS, AXIT, and TIM S.A. Since 1999, he has managed IT and research centers. He created AXIT R&D, which launched a supply chain management SaaS solution.

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