DegradeAlert – AI model quality degradation monitor

Automatically test AI model output quality daily so developers notice silent downgrades

Problem

Many users complain that AI models get worse after updates, yet they lack systematic evidence. Some are manually running daily tests and community votes to track AI degradation. This shows developers are anxious about quality instability but lack automated tools for regular quantitative evaluation.

Solution

A lightweight service that lets users configure a set of standard prompts and evaluation metrics (consistency, hallucination rate, format adherence, etc.) for commonly used models (GPT, Claude, local open-source). Run tests daily and generate quality trend charts, alerting when quality drops below thresholds.

Users

Indie developers building products on AI models, AI app founders, model evaluation enthusiasts

MVP

Support OpenAI and Anthropic APIs; provide 5–10 preset test tasks (JSON format, factual consistency, code correctness); run daily and log results; generate simple trend charts; send email alerts on anomalies.

Revenue

Freemium: free for 1 model, 1 task per day; $19/month for more models, custom tasks, and extended history.

Why now

Model updates are frequent and opaque, and users are increasingly sensitive to quality fluctuations. Manual testing is unsustainable; automated monitoring is a real need. Indie developers can leverage low API costs for recurring value.