I'm Romina Elena Mendez Escobar, currently working as a Cloud & AI Architect. I'm passionate about technology 🚀 and actively involved in social projects 🤝. If you're looking for collaboration on a specific project or need guidance for embarking on a new technological adventure, feel free to reach out to me through any of my social channels.
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In this respository, The final objective will be to transform a set of scientific papers into a knowledge base that can be queried using natural language. This will allow us to ask questions about adverse effects, clinical criteria, study results, and comparisons between different research papers. |
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In this respository, I aim to run a practical benchmark to explore whether TOON could be useful in production pipelines, in what contexts it performs best, and whether it works well across different types of JSON. |
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☕️ From Coffee Products to AI Search: Building a Serverless Semantic Search Architecture with Amazon S3 Vectors and Bedrock Build a serverless semantic search architecture using Amazon S3 Vectors and Amazon Bedrock. This project demonstrates how to generate embeddings from unstructured data, store them efficiently in S3, and query them with natural language. The workflow includes Streamlit integration for interactive searches combined with structured filters. Ideal for anyone exploring Retrieval-Augmented Generation (RAG) and scalable AI solutions. |
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Data-Driven Project Analysis: Analyzing Trello Kanban Projects with AI on AWS Bedrock](https://github.com/RominaElenaMendezEscobar/aws-trello-ai-tutorial)Leverage AI to analyze Kanban project data from Trello. This repository helps detect semantic patterns in tasks, comments, and timelines, providing early warnings for risks or bottlenecks. It integrates AWS services to automate project insights, enabling objective decision-making for distributed teams and high-complexity software projects. Perfect for project managers and data enthusiasts exploring AI-driven project analytics. |
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Use generative AI to monitor brand reputation and transform insights into strategic content. This repository shows how to extract what people are saying online, analyze it semantically, and generate editorial stories that reflect real experiences and concerns. It’s ideal for marketing teams, journalists, and AI practitioners interested in applying AI for content strategy and brand storytelling. |
Create dynamic and interactive diagrams using code instead of graphic tools. This approach simplifies documentation, ensures consistency, and allows for scalable, reproducible visualizations. Great for teams looking to automate visual documentation processes. |
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Convert natural language queries into SQL automatically. This tool leverages AI to connect to databases, generate DataFrames or Plotly visualizations, and provide explanations for SQL queries. Built with Vanna.AI and Python, it’s perfect for developers, analysts, and anyone who wants to make SQL querying more accessible and efficient. |
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Automate and control database schema changes using Alembic and SQLAlchemy. This repository demonstrates best practices for versioning, scripting, and applying migrations safely. Ideal for developers who want reproducible, maintainable, and automated database migration workflows. |
