Predictive analytics
Predictive analytics uses statistical models and algorithms to analyse historical data. Afterwards, it makes predictions about future trends, behaviours, and outcomes. This can include customer churn analysis, fraud detection, and more. The goal is to help organisations make informed decisions while improving outcomes.
Image and speech recognition
Image and speech recognition use machine learning models to process and classify images while also processing audio data. This service can include identifying objects in an image or detecting patterns, while speech recognition can transcribe speech to text and identify speakers.
Natural language processing (NLP)
NLP is the application of AI techniques to analyse, understand, and generate human language. This can include sentiment analysis, language translation, question-answering systems, and more. The goal is to enable computers to understand and respond to human language as accurately as possible.
Recommender systems
Recommender systems use algorithms to personalise recommendations for users. This can include suggesting products to purchase, content to watch, or people to connect with, based on the user's behaviour and preferences. The goal is to improve the user experience and increase engagement.
Anomaly detection
Anomaly detection uses statistical models to identify unusual patterns or events. This can include detecting fraud, network intrusions, equipment failures, and more. The goal here is to identify potential threats and issues early to prevent negative outcomes.
Predictive maintenance
Predictive maintenance uses machine learning models to predict when equipment will fail, allowing organisations to schedule maintenance proactively and prevent downtime. This minimises repair costs and even maintenance costs, while also minimising the likelihood of catastrophic failure.
Customer behaviour analysis
Customer behaviour analysis uses machine learning to analyse customer data. This allows customer behaviour, preferences and habits to be understood. This information can be used to personalise marketing and improve customer experiences.
Fraud detection
Fraud detection uses machine learning algorithms to identify and prevent fraudulent activity, such as credit card fraud or insurance claims fraud. Our machine learning services can also be useful for preventing many other forms of cyberattacks as well.
Sales forecasting
Sales forecasting uses machine learning to predict future sales based on historical data, seasonality, and market trends. Pixelette Technologies uses the latest algorithm models to predict sales and marketing trends for your project.
Supply chain optimisation
Supply chain optimisation uses machine learning to optimise operations and improve efficiency in the supply chain. Our supply chain optimisation services include predicting demand and optimising inventory management for our clients to meet the demands of their customers.
Machine learning can help businesses improve decision-making, automate processes, and drive efficiency. It can also enable businesses to make more accurate predictions, identify trends and patterns. Machine learning can also personalise experiences for customers.
