R-Daniel
Cristina Sarmiento has a diverse work experience, beginning with their current role as COO at R-Daniel since April 2022. Prior to this, they worked as a COO at GaussSoft, starting in May 2007. In this role, they were responsible for formulating, planning, executing, and managing software implementation projects for various companies across different industries. Cristina also handled contractual matters, user documentation planning and control, and managed customer service and support processes.
Before GaussSoft, Cristina held multiple roles at Sistemas Corporativos S.A. Starting in February 2001, they served as a Quality Manager, where they designed, managed, and controlled the Quality Assurance System, leading to ISO9001:2000 certification. Cristina was also involved in defining the company's business strategy and ensuring coherence with the quality system. Eventually, they became the General Manager at Sistemas Corporativos S.A., responsible for developing the company's business strategy, expanding market presence, and establishing a distribution and strategic partner network. Cristina'stenure at Sistemas Corporativos S.A. lasted from April 2004 to May 2007.
Cristina Sarmiento's education history spans over several years. In 1984, they attended Pachas, although no specific degree or field of study is mentioned. From 1991 to 1997, they pursued their Bachelor's degree in Industrial Engineering from Universidad Industrial de Santander. Following this, Cristina completed a Master's degree in Computer Science from the same university between 1998 and 2000. In 2006, they attended INALDE Business School, specializing in Business, Management, and Strategy, where they earned a Postgraduate Diploma in Business.
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R-Daniel
R-Daniel is a ready-to-use specialized AI solution that understands B2B companies and provides them with and incredible edge. This, in the form of a SAAS solution with accesible license fees. R-Daniel automatically understands your business. Its “Master Robot” analyses years of your company sales and profit data and automatically builds, trains, runs, and synchronizes the appropriate scientific and predictive models. It then uses its “business relevance engine” to analyze millions of possible situations and select the best insights, foresights, and opportunities that will result in better company performance. We merge 10+ years of experience in financial and operational big data analytics with the power of Artificial Intelligence and Machine Learning.