The spread of misinformation and disinformation online represents a significant challenge in today's society. This paper proposes implementing a news verifier web application that uses artificial intelligence techniques to determine the veracity of news provided by users. The system consists of three stages: user input validation, selection of relevant sources, and information analysis. We trained a logistic regression model with an in-house dataset of 2000 sentences for input validation. We utilized cosine similarity and FastText for source selection. Finally, a large language model analyzes the context and coherence of selected articles to determine veracity. The transparent presentation of results fosters media literacy. While some implementation details may differ due to time constraints, this paper provides the overall methodology and architecture of the system.