Algorithms that help unlock the full potential of your business, translated into robust, user-friendly software solutions, are milestones that pave the way for your business into the future.Contact us
The insights we gain from your business data allow us to develop algorithms that can form the basis of your future decision-making processes. These include sales forecasting, production process analysis and optimisation, such as avoiding bottlenecks or idle time, predictive maintenance solutions, and innovative solutions for automated customer communications, marketing automation and the automated processing of repetitive tasks. And, of course, the algorithms are monitored and continuously developed so that you can always rely on a reliable data pool and low-maintenance software solutions.
At Limendo, we use different technologies to achieve the goals we set together. Each of these technologies has its own strengths and applications. They are important in different scenarios and for different problems, and in practice they are often used in combination to achieve optimal results.
Below is a list of some of the technologies we have used in our projects:
PySpark is the Python library for Apache Spark, a powerful framework for big data processing and analytics. PySpark enables the seamless integration of machine learning into Spark-based workflows and provides a wide range of algorithms and tools for data analysis and modelling.
Random forest is an ensemble algorithm based on decision trees. It combines multiple decision trees to produce a robust and accurate prediction for classification or regression. Each tree is trained on a random dataset and a random selection of features.
Gradient boosting is an ensemble technique in which multiple weak learning algorithms (e.g. decision trees) are trained in sequence, with each tree attempting to correct the errors of the previous tree. This results in a gradual improvement in model performance.
XGBoost (Extreme Gradient Boosting), a powerful extension of the gradient boosting algorithm. It includes optimisations and regularisation techniques that lead to higher model accuracy and better prevention of overfitting.
TensorFlow is a powerful open source machine learning framework developed by Google. It supports the creation and training of neural networks and deep learning models. TensorFlow provides a set of tools and APIs that can be used by researchers and developers to build complex models for a wide range of applications.
Neural networks are a class of machine learning algorithms inspired by the way the human brain works. They are often referred to as artificial neural networks (ANN) and are an important foundation for many machine learning applications, especially in the field of deep learning.
NLP (Natural Language Processing) is an area of machine learning that focuses on the processing and interpretation of natural human language. It includes technologies such as text analysis, sentiment analysis, named entity recognition and machine translation, which are used to understand, classify and generate text data.
Rasa is an open source platform for building conversational AI and chatbot applications. It provides tools and frameworks for creating chatbot interactions, training NLP models, and managing conversations with users.
ChatGPT is a version of the Generative Pre-trained Transformer (GPT) model developed by OpenAI. GPT is a breakthrough AI model based on the Transformer architecture and trained using supervised machine learning. The "generative" property means that GPT is capable of generating human-like text based on given input. In this case, we are not concerned with developing our own model, but with the right integration and queries/prompts to the AI.
The innovative controlling software by Finanzwerkstatt. For meaningful reporting in the simplest possible way: by clicking one button.
The Microsoft-certified, client-capable Excel add-in for a quick overview of current company figures is equipped with interfaces to the leading ERP systems on the South Tyrolean market and enables automated display of key figures without the need for extensive training. Anytime and anywhere.
wingX was developed in an agile manner over a period of about 1 year and constantly refined. The software was implemented in the MEAN technology stack and subsequently expanded to include AI-based sales forecasting - based on Python.
The complete Business Intelligence package: Data Warehouse, Power BI, Forecast and Analytics for perfect mapping of all business processes and a solid data basis and visualization.
Using the latest technologies, a data pool is created, fed from a wide variety of data sources. Data from all inventory systems has been congruently merged and is now visualized using MS Power BI. The system is also connected to 4 different machine learning models: Sales Forecast in existing branches, Sales Forecast in new locations, Quantity Forecast and Staff Planning. Ongoing implementation over a period of 2 years using various technologies: Databricks, Datalake, Pipelines, Python, SQL, various ML models.
The use of Machine Learning (ML) models opens up a wide range of opportunities for businesses. At Limendo, we have already addressed several of these issues. We also advise companies on which optimisations to start with. As a rule of thumb, you should always start where you can optimise a high cost volume or where there is a high revenue potential.
Here are some of the ways in which machine learning can be used: