CorporateBench: Large-Scale Q&A Benchmarking with Temporal Knowledge Bases
CorporateBench introduces the first large-scale, human-validated Q&A benchmark for enterprise LLMs, tackling the ‘synthetic data’ problem with 230K real documents.
What it does
CorporateBench (CB) is a human-validated, multi-task Q&A benchmark designed to evaluate LLMs on enterprise-scale document collections—where real data is sensitive and synthetic datasets fall short. It tests models across two dimensions: informational equivalence (does the answer match the source?) and contextual grounding (is it relevant to the query?). CB includes over 230,000 documents and 10,000+ questions, validated by humans to ensure quality.
How it applies
Use CB to stress-test your RAG or agentic systems on realistic enterprise data. Its human validation ensures benchmarks reflect real-world complexity, not toy datasets.
Takeaways
- CB is the first human-validated, enterprise-scale Q&A benchmark for LLMs.
- Evaluates both informational equivalence and contextual grounding.
- 230K+ documents and 10K+ questions make it the most realistic corporate benchmark yet.
- Human validation ensures quality and relevance in high-stakes domains.
- Solves the problem of synthetic data bias in enterprise LLM evaluation.
Brendon Score: 8.8/10
- Relevance: 9.0/10 — +2.25
- Depth: 8.0/10 — +2.00
- Actionability: 9.0/10 — +2.25
- Freshness: 9.0/10 — +2.25
- Average: 8.75
- Total (rounded): 8.8/10