Idea
Benchmark platform assessing language agents' expert-level reasoning and reliability in professional domain tasks.
Research Paper
Core Innovation
This paper presents $OneMillion-Bench, a comprehensive benchmark that goes beyond exam-style tasks by incorporating multi-step reasoning, authoritative source retrieval, conflict resolution, and domain-specific constraints. It introduces a rubric-based evaluation focusing on factual accuracy, logical coherence, practical feasibility, and professional compliance to differentiate agent performance at expert levels.
Why It Matters
Enterprises and professionals need AI agents that perform reliably on complex, domain-specific tasks involving nuanced reasoning and compliance. This benchmark enables precise evaluation of agent capabilities in economically critical scenarios, accelerating adoption of AI tools that can handle real-world professional demands at scale.
Market Size (TAM)
$20–50B TAM for AI professional services and domain-specific language agents; $2–10B SAM from legal, financial, healthcare, industrial, and scientific sectors. Driven by demand for reliable AI in complex decision-making and regulatory compliance.
Potential Customers & Pain Points
- Legal firms – Need accurate legal reasoning and compliance
- Financial institutions – Require precise financial analysis and rule adherence
- Healthcare providers – Demand reliable medical knowledge and decision support
- Industrial companies – Seek operationally feasible AI solutions
- Scientific researchers – Need trustworthy evidence synthesis.
Business Model
Offer benchmark access via subscription or licensing to AI developers, enterprises, and research institutions; provide consulting and customization services for domain-specific evaluation and agent tuning.
Competitive Landscape
- MMLU
- BIG-Bench
- HumanEval
- Professional domain-specific AI benchmarks
Implementation Challenges
- High complexity of real-world professional tasks limits immediate agent accuracy
- Need for continuous expert curation and rubric updates to maintain benchmark relevance
- Integration challenges with existing enterprise workflows and compliance standards
Validation Strategy
- Conduct comparative evaluations of leading language agents using $OneMillion-Bench
- Engage domain experts to validate rubric effectiveness and scoring consistency
- Pilot benchmark adoption with enterprise AI teams to demonstrate impact on agent development
Research Paper Overview
$OneMillion-Bench: How Far are Language Agents from Human Experts?
Summary
This paper introduces $OneMillion-Bench, a benchmark of 400 expert-curated tasks across Law, Finance, Industry, Healthcare, and Natural Science to evaluate language agents on complex, real-world professional scenarios requiring multi-step reasoning, authoritative source retrieval, and domain-specific compliance.