ArbitrAI

ArbitrAI is an AI deployment assurance and risk management platform for evaluating LLMs, AI agents, RAG pipelines, vision systems, document-extraction models, and other machine learning workflows. It helps teams define what correct performance looks like, test AI systems against business scenarios, and make evidence-based release decisions.

The platform enables domain experts to create input-and-output evaluation scenarios in business language. These scenarios can be used to test AI responses, compare actual results with expected outcomes, and establish pass/fail release gates for prompts, models, providers, and agent workflows. ArbitrAI also supports AI benchmarking, model comparison, cost-effectiveness analysis, and tracking performance improvements over time.

Designed for product, engineering, risk, and compliance teams, ArbitrAI provides business-readable evaluation results and a continuous audit trail covering scenarios, prompts, models, experiments, and outputs. It supports structured evidence for EU AI Act compliance and can run in a customer cloud or on-premises environment to keep data within the organization’s infrastructure.

ArbitrAI also includes tools for comparing OCR models and providers using business-relevant performance and cost metrics. Its model-provider-agnostic approach supports hosted APIs, self-hosted models, custom or fine-tuned systems, RAG stacks, and agent frameworks.

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