Respan

Respan is an engineering platform that unifies LLM observability, evaluations, prompt optimization, and an AI gateway for development teams. It routes LLM traffic through a single endpoint to provide automatic fallbacks, response caching, and budget limits. Teams can trace AI agent workflows, monitor key performance metrics, and evaluate outputs using LLM judges, code checks, or human reviews.

• Route LLM traffic through a single gateway endpoint to reach 1000+ models across major providers with automatic fallbacks and load balancing.
• Serve repeat requests from response caching to cut cost and latency.
• Set budgets and rate limits per key, per customer, or organization-wide to block requests before spend runs away.
• Grade outputs using LLM judges, deterministic code checks, or human reviewers composed into a single evaluator.
• Sample production traffic and test cases straight from logs or uploaded CSVs to compare scores side by side.
• Monitor requests, errors, cost, latency, and tokens on a single dashboard with alerts sent to Slack, email, or webhooks.
• Trace every LLM call, tool run, retrieval, and agent turn as a span in one trace.

Pros

• Provides automated fallback mechanisms that route requests to a secondary model if the primary model errors or rate-limits.
• Combines multiple evaluation methods including AI judges, code checks, and human review into unified grading.
• Enables granular spend control with rate limits and budgets configurable per key, per customer, or org-wide.
• Captures complete agent execution steps including tool runs, retrievals, and agent turns in a single trace view.

Cons

• Pricing relies on paid tiers with specific log and score caps, requiring enterprise contact for custom volumes.
• Data retention periods vary by plan, with the free tier limited to 7 days of retention.
• Certain compliance features such as a HIPAA BAA require the Enterprise tier.

Respan fits development teams and startups building AI applications that need rigorous observability, routing reliability, and systematic evaluation tools. It is a poor fit for teams not using large language models or those seeking an entirely offline tool without API gateway routing.

Respan offers three tiers. The Free tier costs $0 and includes 100k logs, 1k scores, 5 datasets, 2 evaluators, and 5 prompts. The Team tier costs $199 per month billed yearly and includes unlimited datasets, evaluators, and prompts, plus a private Slack channel and SOC 2 report. The Enterprise tier requires contacting sales for custom packages, volume discounts, custom SLAs, a dedicated support engineer, and a HIPAA BAA.

Unlike standalone observability tools or basic model proxies, Respan combines an AI gateway, prompt management, and multi-method evaluations into a single platform. Rather than just tracking errors or proxying traffic, it directly ties production logs and sampled traffic to automated test sets and side-by-side model comparisons.

Python SDK, JS/TS SDK, OpenAI SDK, OpenAI Agents SDK, Vercel AI SDK, Mastra, LangChain, LlamaIndex, Google GenAI, Mem0, Cognee, AssemblyAI, Linkup, PostHog, OpenAI, Anthropic, OpenRouter, Groq, Fireworks, Together AI, Perplexity, Azure OpenAI, AWS Bedrock, Google Vertex AI, Google Gemini, Nebius AI, and Novita AI.

Respan is worth trying for development teams building AI agents and LLM-powered applications who need an all-in-one solution for traffic routing, observability, and evaluation. The free tier allows teams to test out core features with a capped log and score volume before committing to the Team or Enterprise plans. Teams requiring HIPAA compliance, custom data retention, or dedicated support will need to evaluate the Enterprise tier. Those seeking completely free open-source infrastructure tools will find the freemium model and paid upgrades a key consideration.