AssetOpsBench: Bridging the Gap Between AI Agent Benchmarks and Industrial Reality

PaperBench: Evaluating AI’s Ability to Replicate AI Research

We introduce PaperBench, a benchmark evaluating the ability of AI agents to replicate state-of-the-art AI research.

ScarfBench: Benchmarking AI Agents for Enterprise Java Framework Migration

How Balyasny Asset Management built an AI research engine

By combining rigorous model evaluation, full-platform use of OpenAI, and agent workflows, Balyasny is reinventing investment research.

FrontierFinance: A Challenging Benchmark for Measuring Frontier Intelligence of Finance Agents

AI agents are increasingly deployed for professional investment research, yet no benchmark captures the complexity of the full investor workflow. Existing benchmarks mainly target financial data extraction, a narrow slice that current models have largely saturated, while reference-based metrics and generic LLM-as-a-judge scoring fall short on the open-ended, long-form answers that real analyst queries demand.

AI Agents Are Here. What Now?

How to manage AI investments in the agentic era

Learn how enterprises can manage AI investments in the agentic era by measuring useful work per dollar, improving efficiency, and scaling high-value workflows.