Artificial Intelligence is a computer science discipline that seeks, through models and algorithms, for machines to autonomously imitate human intelligence behaviors; it is considered as the manifestation of intelligence, similar to that of human beings, in a non-human entity.

At the Center we seek to stimulate digital transformation in organizations, contributing to increase the competitiveness and efficiency of their business processes through the incorporation of Artificial Intelligence services and solutions.

Why work with CINTEL?

In CINTEL we lead our own Digital Innovation HUB – “CINTEL DigIHub” that incorporates within the technological ecosystem of services and solutions of Gen AI (Gen AI) with the purpose of providing the best conditions to accelerate business innovation and stimulate the digital transformation of organizations and State entities.

With the integration of CINTEL’s Gen AI solutions in PQRS Management and Business Process Automation, organizations will be able to: analyze large volumes of data and patterns, automate the analysis and design of their processes obtaining a significant improvement in design times and the performance of manual tasks, reduce operational costs and implementation times, improve the quality, efficiency and response times of their processes, increase customer satisfaction and loyalty, and improve their profitability.

At CINTEL we have trained and experienced human talent in the conception and implementation of Gen AI services and solutions, both with our own resources and through our national and international partners, thus enabling a digital environment that meets the human, physical and technical conditions for the business adoption of this type of technological solutions.

What can you find within our Artificial Intelligence services?

  • Technical assistance in the development of solutions and platforms based on Artificial Intelligence:
    • Design of technological architectures.
    • Identification of data sources.
    • Data capture, ingestion, compression, preparation and visualization.
    • Definition of the data catalog.
    • Construction of Artificial Intelligence models.
    • Development of API’s.
    • Design, construction and implementation of Data lake, Pipelines, Data mining, Data science, Geospatial analytics.
    • Image analysis and recognition and remote sensing.
    • Real-time analysis and visualization of spatial data.
  • Planning, design and implementation of advanced solutions in descriptive, predictive and prescriptive analytics.
  • Planning, analysis, design, training, implementation and production of solutions based on Artificial Intelligence through supervised and unsupervised learning to solve needs in automated decisions, computer vision, natural language processing and automation of intelligent processes.
  • Implementation of scenarios for guided analysis with diagnostic, description and prediction algorithms that can be coupled to existing organizational architectures.
  • Artificial Intelligence for decision making in Smart Cities solutions.
  • Use, promotion and training in Artificial Intelligence as an enabling technology for Digital Transformation.
  • Extraction of content from text formats.
  • Automation of reading tasks.
  • Classification and automatic processing of PQRS.
  • Efficient resource allocation and case tracking through generative algorithms.
  • Generating concise summaries and obtaining specific relevant data from the text.
  • Identification of patterns and trends in customer satisfaction using sentiment analysis techniques.
  • Automation in the PQRS response process with Chatbots based on Generative Artificial Intelligence.
  • Prediction of PQRS trends for proactive customer service.
  • Customization of PQRS solutions to offer a better customer experience.
  • Detailed analysis and design of business processes.
  • Clear and accurate generation of process documentation.
  • Analysis of large volumes of data and patterns.
  • Automation with RPA of processes modeled by Generative Artificial Intelligence.
  • Selecting and configuring the appearance and display of Digital People
  • Virtual avatar training according to the organizational context
  • Speech to Speech communication and interaction between people and the Digital People
  • Understanding and responding to conversations in a natural way

This is how we developed our methodology

  1. Definition of the problem and the objectives to be achieved
  2. Collection and preparation of relevant data
  3. Model selection and algorithm development
  4. Model training and performance monitoring
  5. Testing of the model and evaluation of its performance according to defined metrics
  6. Model tuning and optimization
  7. Implementation and operation of the model
  8. Adoption of ethical solution considerations

Some of our success stories