概览
主要功能
- 请求和响应日志记录
- 多步骤 LLM 工作流程跟踪
- 提示和模型性能分析
- 成本和令牌使用跟踪
- 评估和警报工具
- 流行 LLM 供应商的 SDK
价格
- 模型
- $7
- 评分
- 4.8 / 5 (4)
使用场景
调试生产 LLM 问题
工程师使用集中化日志和跟踪快速诊断失败的请求、延迟高峰或在实时 AI 应用程序中意外的模型输出。
跟踪 LLM 成本和令牌使用
团队监测令牌消耗和花费与模型和提示之间，从而控制成本并在它们规模失控之前发现昂贵的工作流。
评估提示和模型性能
使用内置的评估和分析在提示、模型和代理配置之间进行比较，从而能够在质量下降情况下抓住它们前用户使用它们之前
跟踪多步骤代理工作流
使用结构化跟踪以Visual化复杂的代理链，了解每一步如何对最终输出作出贡献，并通过突出失败点识别它们
优点 & 缺点
优点
- 集成式 LLM 日志记录和跟踪
- 快速调试生产 AI 问题
- 跟踪延迟、成本和质量指标
- 与常见 LLM 提供商集成
缺点
- 最适合已在生产中运行 LLM 的团队
- 要求现有代码的Instrumentation
- 较小的生态系统
- 普通 APM 工具的生态系统
对决战绩
在万神殿中参与了 2 对决。
Last 2 battles
评测
4 个评分的平均值。
登录以留下评测。
Years in this space
I've evaluated a lot of these over the years. What stands out here is sDKs for popular LLM providers — handled better than most — and helps debug production AI issues quickly. Worth the time if this is your use case.
Solid for our team
We rolled this out across the team last quarter and helps debug production AI issues quickly. Tracing for multi-step LLM workflows fits neatly into how we already work, and sDKs for popular LLM providers removed a step we used to do by hand. Smaller ecosystem than general-purpose APM tools, which is the main caveat, but it has held up under daily use.
Years in this space
I've evaluated a lot of these over the years. What stands out here is evaluation and alerting tools — handled better than most — and tracks latency, cost, and quality metrics. Worth the time if this is your use case.
Compared a few options
Evaluated this against two competitors. Where it wins: tracing for multi-step LLM workflows and unified view of LLM logs and traces. Where it lags: most useful for teams already running LLMs in production. On balance the feature set — especially evaluation and alerting tools — justifies the 4 stars for our use case.
问答
What are the limitations of Keywords AI?
Cons include being most useful for teams already running LLMs in production, requiring instrumentation of existing code, and having a smaller ecosystem than general-purpose APM tools.
Asked by Ximenez Alvarado · Sep 2, 2025
What are the pros of using Keywords AI?
Pros include a unified view of LLM logs and traces, quick debugging of production AI issues, and tracking of latency, cost, and quality metrics.
Asked by Kalinda Reddy · Aug 12, 2025
What features does Keywords AI offer?
Key features include request and response logging, tracing, prompt and model performance analytics, cost and token usage tracking, and evaluation and alerting tools.
Asked by Gunnar Eriksson · Jul 4, 2025
What is Keywords AI used for?
Keywords AI is a developer platform for monitoring, debugging, and improving AI applications built on large language models.
Asked by Dara Fitzgerald · Jun 29, 2025
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统一网关，监控、调试并优化跨供应商的 LLM 应用。
