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// BENCHMARKS

Introducing Custom Benchmarks By Runloop

Evaluate AI coding agents with precision using Runloop's Public Benchmarks. Our platform offers standardized performance metrics that help developers and researchers assess capabilities across different tasks and domains.

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Use Cases

Turn your domain expertise into automated, high-margin AI verification standards across critical industry tasks.

Code Security & Exploit ID

Test for robust code safety. Security experts create benchmarks that generate vulnerable code to continuously score an LLM's or security tool's ability to identify and correctly fix exploits.

Use Case

Software Development

Proprietary Investment Strategy

Safeguard unique alpha. Financial analysts define benchmarks to stress-test AI trading agents against proprietary strategies and high-volume alternative data, ensuring logic and risk adherence.

Use Case

Fintech

Domain-Specific Multilingual Translation

Guarantee technical accuracy worldwide. Domain experts establish benchmarks that verify an AI translator's precise use of industry-specific and technical terms across multiple languages

Use Case

Multilingual/Global

Regulatory Compliance (AML/KYC)

Automate compliance verification. Experts define logic to test an AI agent's ability to flag complex, suspicious transactions and adhere to strict AML/KYC regulations

Use Case

Fintech

Clinical Documentation Accuracy

Ensure critical coding precision. Clinicians build benchmarks that verify an AI agent's consistent and accurate assignment of medical codes (e.g., ICD-10) and extraction of key patient dataEvaluates AI agents´ability to solve real-world GitHub issues by producing code edits as patch files

Use Case

Healthcare

Contractual Risk Assessment

Verify deep legal understanding. Legal experts create benchmarks to test an AI's precision in identifying, summarizing, and scoring proprietary risk clauses within complex M&A or sector-specific contracts.

Use Case

Legal/Structured Data