AI and Generative AI offer countless opportunities to optimize business processes, drive innovation, and unlock new potentials. Whether it’s automation, data analysis, or personalized customer experiences – we help you discover and successfully implement tailored AI solutions for your specific requirements.
synvert is perfectly positioned as a leader in Cloud Data & AI to design and implement your AI use cases.
With our extensive experience in Cloud & Analytics, we recognized the potential of AI and Generative AI early on and have successfully completed numerous AI projects with our clients. Our consultants leverage our GenAI Accelerator to bring your projects to production in a short time, adopting a technology-agnostic approach. This enables us to work with major platforms and tools from OpenAI, Anthropic, and Azure while also utilizing open-source models and solutions if they better address your specific use case.
Development of a tailored LLM for automatic categorization of claim types and extraction of relevant details from insurance claim reports – for more efficient analysis and faster claims processing.
A Retrieval Augmented Generation (RAG) based chatbot makes insurance documents for life, health and property insurance intelligently searchable and provides AI-supported, precise answers in natural language. It extracts relevant passages, understands complex queries and improves efficiency in customer and case processing.
Implemented a staged forecasting model to continuously predict total demand in online commerce.
Developed a chatbot supporting technical engineers in creating technical documentation.
Prediction of oil properties to optimise refinery configuration for maximum base oil yield in minimal time.
Prediction of failures on railroad switches based on historical and current data to optimise maintenance and replacement.
Automated traffic report processing using Large Language Model (LLM) based systems.
Implementation of a “Invoice to cash” prediction model to predict the delay in payment of pending invoices for a world-class maritime logistics and port operations organisation.
Natural Language Processing in Automotive Reporting. An ingestion mechanism including OCR digitization, artefact removal and text cleansing was created and has since been fed well over a million reports. As a final step in the NLP pipeline, topic modelling was used to tag the documents according to their content.
Automatic classification of cars by their model – A deep convolutional neural network was trained to identify car types. It can identify roughly 200 different types of cars with near-human level accuracy.
The vision was to develop a predictive maintenance platform to save costs by reducing expensive repairs. The ML model is able to predict potential problems for a given machine based on many different characteristics (when it was manufactured, when it was sold, components, etc.)
Prediction of customer churn in a subscription-based donor model for a global non-profit organisation.
Automated predictive model for pricing optimisation over different sales periods for a multinational retailer headquartered in Europe.
Development of a system in which promotional offers could be both personally tailored and reliably delivered to customers. The system operates on a points-based system in which customers who share more data by participating more are rewarded.
Machine learning generated customer segmentation for a data-driven retail experience for a major fuel retailer and distributor in the Middle East.
Enabled smarter targeting of B2C Rewards customers for an oil & gas distribution company in the Middle East through Machine learning based customer segmentation.
Rock classification using computer vision to detect drilling exploration sites for a leading energy producer in the Middle East.
Managed the end-to-end operationalisation of Machine Learning models for network security use cases using Cloudera Data Science Workbench (CDSW), for a leading public petroleum and natural gas company in the Middle East.
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