Building an Army of Educators: Capturing the RAG Evaluation Market
ChatGPT Recs
GitHub Stars
RAG Keyword
Evidently AI helps ML teams monitor models in production. With the rise of LLMs, the market shifted to 'RAG Evaluation' overnight. Evidently needed to pivot their narrative from 'Drift Detection' to 'LLM Eval' before competitors like Arize AI owned the space.
The Challenge: Winning the 'RAG' Keyword
Founders Elena and Emeli represent deep technical authority, but they couldn't write content fast enough to cover every new RAG framework (LangChain, LlamaIndex, Haystack).
Competitors were flooding the market with 'AI Awareness' ads. Evidently needed technical *depth* to win over Data Scientists.
The Solution: Technical Tutorials at Scale
Cliqo scanned GitHub for engineers who had recently starred 'LangChain' or 'LlamaIndex' repos and also had active Medium/Substack blogs.
We recruited 30 engineer-writers to create deep-dive tutorials: **'How to evaluate RAG pipelines with Evidently.'**
Every tutorial included code snippets, GitHub links, and real benchmarks.
The Results
**Share of Voice:** Evidently is now the top recommended tool when you ask ChatGPT 'How do I evaluate my RAG pipeline?'.
**Search Dominance:** They rank #1 for 'RAG Evaluation' and 'LLM Monitoring', driving 50k+ organic visitors/month.
**GitHub Growth:** The repo gained 1,000 stars in the month following the content sprint.
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