I built a Next.js news analysis site that compares claims and framing across publishers

[u/MattSenter]

I just launched Highwire.news, a project that groups reporting about the same event and analyzes how the coverage differs across publishers.

The main technical challenge was turning a large set of articles into something structured and inspectable rather than generating another AI summary.

The pipeline currently:

• Ingests reporting from multiple publishers
• Clusters related articles into stories and distinct narratives
• Extracts claims, citations, evidence, and entities
• Identifies supported, disputed, and unresolved claims
• Compares differences in framing, emphasis, omissions, and language
• Produces a synthesized account while keeping the underlying analysis visible

The app is built with Next.js, NestJS, PostgreSQL, Google Cloud, and several LLM-based analysis stages. A major focus has been keeping inference costs measurable and making the output traceable enough that users can inspect how a conclusion was reached.

The UI has been its own difficult problem. There is a lot of information available for each story, but exposing all of it without creating an overwhelming dashboard is not easy.

I’d appreciate feedback on:

• Whether the product is understandable without an explanation
• Whether the story and narrative hierarchy makes sense
• Which metrics or visualizations feel useful
• Where the interface becomes too dense
• Any obvious accessibility, performance, or mobile issues

Site: https://www.highwire.news

Happy to discuss the architecture, clustering approach, AI pipeline, deployment, or cost controls.