Offering Expertise in Data Analytics and Software Development

Dogus Technology has developed many R&D projects for different sectors with its expertise in Machine Learning, Deep Learning, Natural Language Processing, Blockchain, SW Platform Development and Web/Mobile Applications. There are 4 R&D projects completed successfully that has been funded by TÜBİTAK, the national official institution of Turkey:

Optimization/Improvement of Spare Part Warehouse Processes with Machine Learning Methods (DIGITAL WAREHOUSE): An order picking algorithm, order picking time prediction model and simulation model has been developed by Dogus Technology.

Automotive Support Channels Dialogue Management System – Natural Language Processing (ZEYREK): Dogus Technology has developed a smart chatbot for automotive companies using natural language processing (NLP), machine learning and deep learning.

A Next Generation Framework for Building Scalable, Cloud-Native, Containerized, Distributed Micro-Services Applications (INDIGO): Dogus Technology has developed a cloud native, containerized and distributed micro-services framework that aims to speed up the software developing processes.

Operational Fleet Rental Decision Support System (PASCAL): Dogus Technology has developed decision making support system that predicts the RV-Residual Value the fleet rental and second-hand vehicle sales process.

There are three ITEA projects that have been labelled and currently in the process of development:

Optimal Management of Demand (OMD): Dogus Technology contributes to the project by developing digital assistants using natural language processing (NLP), machine learning and deep learning.

Environment Adaptive Recommendation System (EARS): Dogus Technology will contribute to the project by developing a recommendation system, which will be able to sense & understand customer needs and adapt itself to needs of media sector.

Cognitively Smart Assistant in Phygital Environment (CAPE): Dogus Teknoloji will contribute to the project by developing a recommendation system for providing personalized shopping experience to customers in retail sector.

There are currently two EUREKA projects which were funded under different EUREKA calls and currently ongoing:

Solar Energy Management Optimization (SOLARPULSE): Proposed under EUREKA’s Turkey-Spain Call. Dogus Technology will develop ML/AI algorithms in order to predict the amount of electricity production and consumption on its data center. Moreover, the results of the model will be supplied to a platform which will also be developed by Dogus Technology. This platform will be able to produce what-if scenarios for different solar panel types or numbers, as well as for different types or numbers of electronic devices. End users will be able to see the electricity production and consumption values in these alternative configurations.

Agriculture’s Digital Analyzer of Production, for Phosphorus Efficiency (AgAPP-e): Proposed under EUREKA’S Sustainability Call. Dogus Technology will contribute to the project by developing machine learning algorithms and the decision-making support system that predicts the macro-level P stock in soil at a specific region.

Lastly, there are three ITEA-labelled projects that have been approved by TÜBİTAK and is waiting for international consortiums to finish their approval process:

Improved efficiency in automated medical reporting to enhance doctor and patient experience (MEDISPEECH): MediSpeech will present an integrated, digital IT ecosystem for automated medical reporting with proven added value in the clinical practice, in the shape of platform infrastructure that supports the transformation of the organisation-centred healthcare model into a patient/doctor-centred model. Dogus Teknoloji will contribute to the project by developing a clinical decision support system using reinforcement learning.

Medical GPT Revolutionizing Healthcare with Ethical AI (MedGPT): The MedGPT project is addressing privacy and ethical concerns by embedding ethical AI and European GDPR & MDR compliance into its platform, utilising European-based LLM with the aim to set the standard for Medical GPT applications globally. Dogus Teknoloji will contribute to the project by developing a clinical decision Support system using reinforcement learning for children that have diabetes.

FERtigation Irrigation DEcision Support System (FERIDE): FERIDE will deliver platforms and frameworks that will enable precise application of water-soluble fertiliser through sprinkler and drip irrigation. Dogus Teknoloji will contribute to the consortium by developing ML/AI algorithms to predict the water requirement of the soil in a certain region.