Real-time response detection
Scores each AI response for trustworthiness so the system can decide whether to answer, hand off to a human, or use a fallback flow.
Piattaforma di affidabilità AI per rilevare e correggere gli errori degli agenti
Cleanlab is an AI reliability platform that helps teams detect incorrect responses from AI agents and remediate them before they reach users. Its homepage frames the product around keeping mistakes away from customers by adding safety, control, and trust to existing AI systems and knowledge bases.
The product is presented as an independent layer that works with any AI system. It supports real-time detection with trust scores and guardrails, plus a remediation workflow where subject-matter experts can supply expert answers, review unresolved questions, and help correct failures at the source.
Scores each AI response for trustworthiness so the system can decide whether to answer, hand off to a human, or use a fallback flow.
Flags issues such as hallucinations, missing context, wrong context, knowledge gaps, policy violations, retrieval errors, and malicious use.
Lets SMEs provide answers directly so unresolved questions can be corrected in production without retraining or fine-tuning.
Groups and prioritizes recurring failures using trust scores and user impact, helping teams focus on the most important problems first.
Tracks prompts and flagged or corrected responses so teams can monitor where issues occur and how often they are resolved.
Supports a configurable quality workflow with 15+ evaluation models, 5 quality settings, and latency as low as 300 ms according to the Detect page.
Use trust scores and guardrails to decide when an AI agent should answer directly and when it should escalate to a person or fallback flow.
Let non-technical subject-matter experts patch incorrect answers in live systems and reduce the need for engineering intervention.
Review unresolved questions, group recurring failures, and identify whether the issue comes from the LLM, retrieval layer, or source data.
Track prompts and corrected responses to monitor how often agents produce flagged outputs and where quality problems cluster.
Cleanlab is designed to detect incorrect AI responses in real time and then help teams remediate them through a human-in-the-loop workflow. The Detect page focuses on scoring outputs for trustworthiness, while the Remediate page focuses on SME review and expert answers.
The source describes two deployment options: VPC deployment within your own cloud and SaaS access without managing infrastructure. It also says the product works with any AI system and knowledge base as an independent safety layer.
Cleanlab is built for teams that need AI responses to be accurate, safe, and aligned with business standards, including customer support and employee-facing AI agents. The homepage also positions it for high-stakes AI applications where incorrect answers should not reach users.
The site says getting started takes just a few lines of code, and the Remediate page notes that Enterprise API connectors can let teams work in preferred applications such as Slack. The Detect page also points to docs for setup and integration details.
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