Specific Labs

Convert real company operational data into benchmarks and evaluation datasets for autonomous domain agents

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You can use Specific Labs to transform real enterprise workflows and private codebases into training data and benchmarks for domain-grounded autonomous agents. The service captures complex workplace decisions, exceptions, and handoffs from existing company systems rather than relying on synthetic or clean generic datasets. Through real-world testing environments like Real-SWE, you can evaluate frontier models against actual licensed production codebases to see how effectively they resolve genuine engineering tasks. This allows organizations to build more dependable agents tailored to specific corporate operational environments.

What Specific Labs does

Benchmark frontier language models on private corporate codebasesMeasure agent resolution rates on complex software engineering issuesRequest sample access to enterprise benchmark datasetsAnalyze cost efficiency across different model generationsTurn unstructured internal handoffs into structured training recordsTrack autonomous agent performance over repeated execution runsBenchmarking frontier models on licensed private production codebasesCapturing messy enterprise operational decisions and exceptionsReal-SWE benchmark measuring model resolution rates on real codeCost estimation tracking per automated coding runPass rate comparisons across multiple model runs per taskCustom training datasets generated from domain-specific workflowsResearch datasets derived from live autonomous agent execution