đź’ˇ SaaS Idea: Model Drift Watch: Daily LLM Benchmarking
Runs the same prompts across multiple LLMs daily and shows changes in outputs, quality, safety, and cost; alerting for regressions and dashboards for enterprises relying on LLMs.
Platform: web
Why it's a good idea?
1. Signals of the Problem in the Wild
- Reddit thread supplied by user already shows developers explicitly asking for “a website that runs the same prompts on different LLMs every day”. 100+ up-votes and comment discussion (r/ChatGPTCoding, July-2025).
- Dozens of fresh Reddit posts complain about GPT-4/4o “getting worse”, “performance drop”, “secretly downgraded”, etc. (search query: chatgpt performance change reddit). 10+ high-engagement threads from 2024-2025 signal pain around undetected model regressions.
2. Keyword Demand
| Keyword |
Monthly volume |
Difficulty |
Passes 500+ & <30? |
| llm eval |
1 300 |
28 |
âś… |
| llm evaluation framework |
390 |
13 |
— (<500 but easy) |
| llm benchmark |
3 600 |
38 |
❌ (volume ok, difficulty high) |
| llm benchmark comparison |
90 |
25 |
— (low vol) |
| llm leaderboard |
6 600 |
62 |
❌ |
| There is at least one head keyword (“llm eval”) that meets the rule of thumb (1 300 searches, KD 28). Long-tail keywords add extra ~2-3k searches / month. |
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3. Competitive Landscape (SERP & web search)
Commercial or semi-commercial offerings that touch the space:
- LiveBench.ai...
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