Respan Gateway
One AI gateway with built-in observability and evals
Respan Gateway launched on June 11, 2026 with 352 votes, #54 of 22,647 launches that month and more than 99% of that year's launches.
In plain words
Respan Gateway is an AI gateway that routes applications to over 1,000 AI models through a single endpoint. It provides built-in observability, fallbacks, retries, caching, spend limits, and full call traces to keep production AI systems reliable and controlled. The platform combines gateway routing, monitoring, evals, prompt management, and cost controls in one place, eliminating the need to integrate multiple separate tools for production debugging and management.
written from the facts on this page · September 2026
From the sources
Respan AI Gateway connects your app to 1,000+ AI models through one endpoint. But routing is the easy part. Respan keeps production AI reliable and under control with fallbacks, retries, caching, spend limits, alerts, and full traces for every call. Gateway, observability, evals, prompt management, monitors, and cost controls all run on one platform, so you do not need to stitch together five tools to debug production.
Route LLM traffic through one OpenAI-compatible endpoint on Respan with 1,000+ models, failover, caching, per-key limits, and request metadata.
Unified router or provider passthrough for 1,000+ models, with failover, response caching, warn/block limits, and metadata on every logged request. Point the SDK you already use at one endpoint to reach 1,000+ models, with automatic fallbacks, response caching, and spend limits built in. Send every request to one endpoint, reach 1,000+ models across every major provider, and switch between them by changing a single word. List the models to fall back to, and Respan moves to the next the moment one errors or rate-limits, so an outage never takes you down. Cache a request and its response, then serve the same call again instantly, cutting the cost and latency of every repeat to nothing. Set…from respan.ai
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TrueFoundry AI GatewayDec 2025 · truefoundry.com · ▲315Many teams connecting LLMs to external tools eventually encounter the same architectural issue: as more tools and agents are added, the integration pattern becomes an N×M mesh of direct connections. Each agent implements its own auth, retries, rate limiting, and logging; each tool needs credentials distributed to multiple places and observability becomes fragmented. We built LLM gateway with this goal to provide a single place to manage authentication, authorization, routing, and observability for MCP servers, with a path toward a more general agent-gateway architecture in the future. The…

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