Idea
Benchmark revealing LLM gaps in complex business query understanding for smarter decision tools.
Research Paper
Core Innovation
This paper introduces CORGI, a benchmark with synthetic business databases and multi-level query complexity, unlike prior benchmarks focused on factual retrieval. It challenges LLMs with causal reasoning, temporal forecasting, and strategic recommendation tasks, exposing their limitations in real-world business intelligence scenarios.
Why It Matters
Businesses rely on accurate data-driven decisions, but current AI models struggle with complex, multi-step business queries involving forecasting and recommendations. CORGI benchmarks these challenges, enabling development of AI tools that better support strategic business intelligence, improving decision accuracy and operational efficiency at scale.
Market Size (TAM)
$20–50B TAM for business intelligence and analytics software; $2–10B SAM from enterprises adopting AI-driven decision tools. Driven by increasing demand for AI-enhanced data analysis and strategic forecasting.
Potential Customers & Pain Points
- Enterprises–Need AI that understands complex business queries
- BI software vendors–Require benchmarks for advanced model evaluation
- Data scientists–Lack realistic datasets for business domain model training
- Consulting firms–Need tools for strategic data analysis.
Business Model
Open benchmark and evaluation platform with potential for licensing enhanced datasets and enterprise-grade AI model integrations.
Competitive Landscape
- BIRD benchmark
- Spider benchmark
- Text-to-SQL datasets like WikiSQL
Implementation Challenges
- LLM limitations in causal and temporal reasoning
- Complexity of real-world business data modeling
- Adoption inertia in enterprise AI tools
Validation Strategy
- Public dataset release and leaderboard for community benchmarking
- Partnerships with BI software vendors for real-world testing
- User studies with enterprise data teams to assess impact on decision workflows
Research Paper Overview
Agent Bain vs. Agent McKinsey: A New Text-to-SQL Benchmark for the Business Domain
Summary
CORGI is a new text-to-SQL benchmark designed for real-world business contexts, featuring synthetic databases inspired by companies like Doordash and Airbnb. It includes questions across descriptive, explanatory, predictive, and recommendational categories, requiring causal reasoning and strategic planning. The benchmark reveals significant performance gaps in LLMs on complex business queries, highlighting the need for improved business intelligence tools.