Respan is an AI gateway and observability platform that combines routing, tracing, evaluations, prompts, and cost controls for AI applications.

Who should use Respan?

It is best for developers and AI teams running agents or LLM applications that need centralized production monitoring and control.

Can Respan route models?

Yes. Respan provides gateway features for routing model requests and managing providers across AI applications.

Does Respan support evaluations?

Yes. Teams can use datasets and evaluators to measure AI behavior and identify quality regressions.

Can Respan track AI costs?

Yes. Cost and usage visibility are part of its production observability and governance workflows.

What should buyers consider?

Review provider support, trace volume, retention, governance needs, model costs, and deployment requirements before adoption.

Respan

AI gateway, tracing, evaluations, and observability platform for agents.

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What is Respan?

TL;DR

Respan is an AI gateway and observability platform for agents and LLM applications, combining routing, tracing, evaluations, prompts, cost controls, retries, fallbacks, and production monitoring in one layer.

Trace, evaluate, and monitor AI agents
Unified gateway for 500+ models and providers
Prompt management, datasets, and evaluators

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About

Respan, formerly Keywords AI, is an AI gateway and observability platform for developers building agents and LLM-powered applications. It helps teams route model requests, trace agent workflows, evaluate outputs, monitor costs, manage prompts, and improve production AI systems from one place. The platform includes logs, scores, datasets, evaluators, prompt management, gateway features, retries, fallback, request caching, load balancing, rate limits, and spend controls. This makes it useful for AI products that need both model access and operational visibility. Respan is especially valuable for SaaS founders and technical teams building agents, chatbots, internal copilots, support automation, research tools, and workflows that rely on multiple model providers. Instead of managing separate observability, gateway, and eval systems, teams can use one layer for tracing and control. For FutureStack, Respan fits Developer Tools because it supports production AI infrastructure. It is best for developers and founders who want better visibility, reliability, and cost control across AI agent and LLM application workflows.

Use Cases

AI Gateway

Route model requests through one gateway while applying retries, fallbacks, caching, and provider controls.

Agent Observability

Trace agent runs, tool calls, model requests, and retrieval steps to debug production behavior.

AI Evaluations

Score model and agent outputs against datasets and evaluation rules to detect regressions.

Cost Governance

Track spend and apply usage controls across models, users, teams, and applications.

Key Features

Trace, evaluate, and monitor AI agents
Unified gateway for 500+ models and providers
Prompt management, datasets, and evaluators
Cost tracking, alerts, caching, retries, and fallback

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