VECTOR Labs

VECTOR Labs.ai is a technology company that provides data science, machine learning and software development services. The organisation lists headquarters in Sofia, Bulgaria and an office presence in Manchester, England, indicating operations in Europe.

Services and Capabilities

• Data and analytics: design and deployment of data architectures that integrate multiple sources (ERP, CRM, sensor streams, external datasets), ETL pipelines and analytical dashboards.
• AI and machine learning: development of ML models from discovery through proof-of-concept, MVP and production, including model training, validation and production inference pipelines.
• Software development: full-stack web and mobile application development, back-end and front-end engineering, QA, DevOps and security practices.
• Product development: end-to-end product delivery including POC, MVP and scale-up phases, UX and product management support.
• Digital transformation: system modernisation projects that combine software engineering, data engineering and process change to support operational digitisation.
• Strategy and consulting: technology and data consultancy, roadmaps for cloud adoption, analytics and organisational data practices.

Industry Focus The company documents work across healthcare and pharma, manufacturing, education, banking and financial services, travel and retail. For healthcare and pharma it has developed predictive models, clinical research models and telemedicine platforms; in manufacturing it has delivered computer vision and maintenance management systems; in education it has built learning management and gamification platforms and museum video/chatbot platforms; in banking and fintech it has delivered propensity-to-buy, probability-of-default, churn prediction and offer-optimization models; in travel it rebuilt a reservations exchange platform and CRM integrations.

Technology and Delivery Approach Projects commonly use Python for back-end and data work, Django for web back ends, React or Angular for front ends, AWS for cloud infrastructure, and ML frameworks such as Keras and TensorFlow. Computer vision work uses OpenCV, YOLO and SSD; search and analytics use ElasticSearch and Kibana. Delivery patterns include discovery phases, automated testing, POC/MVP iterations, champion–challenger testing, API-based integration, CI/CD and production model pipelines. Research initiatives include federated learning experiments (euroCat) and clinical predictive modelling with evaluation by AUC metrics.