Cubet

Cubet is a technology services company providing custom software development and AI-enabled product engineering. The company describes itself as a provider of AI, data intelligence, and digital transformation services and reports working with clients across multiple regions, including projects in Africa and customers based in Europe and other overseas markets. Headquarters country: not stated in the source.

Services and Capabilities

• Data and AI development: delivery of machine learning models, data engineering pipelines, and AI-powered automation components.
• Generative AI and LLM work: consulting, model training, and integration of large language models into applications.
• Conversational AI and AI agents: design and deployment of chatbots and voice agents for customer qualification and meeting scheduling.
• Product engineering and cloud enablement: end-to-end product development including cloud-hosted web and mobile systems, DevSecOps practices, and continuous delivery.
• Analytics and business intelligence: dashboards, data visualization, predictive analytics, and recommendation engines for real-time personalization.
• IT outsourcing and managed delivery: multi-year development engagements, team augmentation, and ongoing support for client platforms.

Industry Focus

• Healthcare: development of electronic medical record components and AI assistants integrated into digital health platforms to support clinical decision-making.
• Education / EdTech: construction of AI-powered learning platforms with personalized, interest-based student experiences for underserved regions.
• Retail and E-commerce: implementation of conversational sales assistants and real-time recommendation engines to increase conversions and average order value.
• BFSI and Enterprise SaaS: enterprise product development, cloud enablement, and data-driven features for software platforms.
• Hospitality and other verticals: platform development and integration services tailored to sector-specific workflows.

Technology and Delivery Approach

• Integration of AI across systems and workflows, including embedding intelligence into existing applications and data stores.
• Use of data engineering and analytics pipelines to enable real-time personalization and predictive features.
• Cloud-native delivery and DevSecOps practices for continuous integration and deployment of web and mobile products.
• Conversational interfaces and AI agents built with natural-language capabilities for customer engagement and automation of routine tasks.
• Engagement models that include multi-year partnerships, team augmentation, and managed delivery with a focus on iterative product development and measurable outcomes.