Keywords AI

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LLM engineering platform for routing, observing, evaluating, optimizing, and deploying AI applications and agents.

网站：https://www.keywordsai.co/
收录时间：2026年7月13日
月访问量：
2.7K
社交与联系：
LLM gatewayLLM observabilityAI evaluationAI agentsPrompt engineeringModel monitoring
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Keywords AI
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工具信息

什么是 Keywords AI？

Respan is an LLM engineering platform that provides a unified gateway for managing LLM traffic, monitoring production usage, evaluating outputs, and improving AI application reliability. The supplied official sources redirect from Keywords AI to Respan, which is the current product branding shown in those sources.

核心功能

  • LLM gateway

    Route OpenAI-style calls to more than 500 models through one API, use provider passthrough endpoints, and log every request.

  • Fallbacks and load balancing

    Configure fallback models, balance traffic across API keys, and retry requests with backoff when models encounter errors or rate limits.

  • LLM observability

    Capture gateway calls as trace trees with latency, prompts, tool calls, responses, metadata, and customer identifiers.

  • Usage monitoring and alerts

    Track requests, tokens, errors, latency, and cost by model, API key, and product traffic, with Slack, email, or webhook notifications.

  • Spend controls and caching

    Set soft warnings or hard caps per API key, configure threshold alerts, and cache repeated prompts to help reduce cost and latency.

  • Evaluation workflows

    Combine rule checks, LLM judges, and human review in evaluation workflows, including evaluations of sampled production traffic.

  • Prompt and model experiments

    Create datasets from production traces or CSV files and compare prompt and model variants before deployment.

  • Agent tracing

    Capture agent prompts, tool calls, and responses with contextual information for analyzing agent behavior.

使用场景

  • #1

    LLM traffic routing

    Route application requests across multiple model providers and models through one gateway.

  • #2

    Production AI monitoring

    Monitor model usage, cost, latency, errors, and token consumption in production.

  • #3

    AI quality evaluation

    Evaluate AI outputs with automated checks, LLM judges, human review, and production sampling.

  • #4

    AI application experimentation

    Compare prompts and models using datasets derived from traces or CSV files before shipping changes.

  • #5

    AI agent debugging

    Inspect agent traces, including prompts, tool calls, responses, and related context.

适用人群：AI application engineersML engineersProduct teamsTeams building AI agentsFounders

定价方案

The official source includes a Pricing link, but pricing details are not clearly published in the supplied snapshot.

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常见问题

What is Respan?
Respan is an LLM engineering platform for routing model traffic, observing production usage, evaluating AI outputs, running prompt and model experiments, and tracing AI agents.
How does the LLM gateway work?
The gateway routes OpenAI-style calls to more than 500 models through one API. It also supports provider passthrough endpoints and logs requests.
Can Respan monitor production AI usage?
Yes. It tracks requests, tokens, errors, latency, and cost by model, API key, and product traffic.
Does Respan support model fallbacks?
Yes. Respan supports fallback models, load balancing across API keys, and retries with backoff for model errors and rate limits.
What evaluation methods does Respan support?
Evaluation workflows can combine rule checks, LLM judges, and human review. Evaluators can also be applied to sampled production requests.
Can Respan trace AI agents?
Yes. It captures agent prompts, tool calls, responses, and contextual information for analyzing agent behavior.
What is Respan's pricing?
Pricing is not clearly published in the supplied official snapshot.

Keywords AI 联系方式与社交媒体

访问官方网站

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工具信息

定价模式Unknown
分类检测工具
二级分类
LLM gatewayLLM observabilityAI evaluationAI agentsPrompt engineeringModel monitoring
语言英语
最后更新2026年7月16日
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