Metagenomics studies the totality of genomes of all species in a microbial community. It is a young, growing field with medical, industrial, and ecological applications. Abundant metagenomic data is being produced today, but there is a lack of interpretation and visualization tools. The aim of this project was to create Nanometa Live: a user-friendly, real-time data processing pipeline and graphical user interface that enables visualization of the general species content in a sample, as well as detection of a set of predetermined pathogens. The pipeline was created using Snakemake, with classification by Kraken 2, and sequence validation by BLAST, with the input of the pipeline being fastq batch files from an Oxford Nanopore. The interface was coded in Python using the framework Dash, and utilizes the data produced by the pipeline to visualize results. A Sankey plot and a list of most abundant taxa displays the general species content, while a separate table and a gauge, colored to show the pathogenicity of the sample, displays the user-determined pathogens that the program looks for. Further exploration of the species composition is enabled by a sunburst plot and an icicle chart. Nanometa Live is a fully functioning prototype and can be considered on par with existing tools when it comes to analysis speed, computer requirements, and general user-friendliness. Its strengths are ease of interpretation and flexibility in visualizations, with weaknesses being lack of functionality, such as antibiotic resistance detection, and imperfections in code, structure and packaging.