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Respan

Free

Unified LLM engineering platform for observability, evaluations, prompt optimization, and AI gateway services.

Quick Facts

Pricing
Free
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Added
Mar 2026
Official URL
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Tool overview

Overview

Respan is a unified LLM engineering platform that helps teams build, ship, and operate reliable AI applications at scale. Instead of stitching together separate tools for logging, evaluation, prompt iteration, routing, and model access, Respan centralizes the full lifecycle of large language model development. With Respan, developers get deep observability into prompts, responses, errors, and latency across all their LLM providers. Built‑in evaluations, guardrails, and regression testing make it easy to compare models, validate changes, and prevent quality drift in production. A powerful prompt and workflow editor lets you experiment quickly while keeping a clean version history of what goes to production. Respan also acts as an AI gateway: connect once and securely route traffic to multiple LLMs, switch providers without code changes, and enforce quotas, authentication, and compliance policies in one place. Whether you are building chatbots, internal copilots, or complex agents, Respan gives you the infrastructure to move from ad‑hoc prototypes to robust, maintainable systems. Designed for modern engineering teams, Respan offers a free tier so you can start instrumenting, evaluating, and optimizing your AI stack in minutes—without rebuilding your existing architecture.

Screenshots

Respan screenshot 1

Features

  • Unified LLM observability
  • Centralized evaluations & testing
  • Prompt and workflow optimization
  • Multi-provider AI gateway routing
  • Versioning and experiment tracking
  • Guardrails and safety controls
  • Performance and cost analytics
  • Developer-friendly APIs & SDKs

Tags

AI Developer Tools
Large Language Models (LLMs)
AI Monitor
Prompt Engineering
AI Agent

Use Cases

  • Monitor and debug production LLM applications with full visibility into prompts, responses, latency, and failures across providers.

  • Continuously evaluate and compare different LLMs or prompt versions to choose the best-performing configuration for your use case.

  • Optimize prompts and agent workflows collaboratively, then safely roll out changes with version control and regression tests.

  • Use Respan as a single AI gateway to route traffic between vendors, enforce authentication, and manage rate limits and quotas.

  • Instrument internal AI copilots to track quality, spot regressions, and justify model or provider changes with data.

Frequently Asked Questions

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