Respan Gateway

Respan Gateway is an AI observability gateway that enables teams to route, observe, and evaluate every LLM call through a single unified API. Built for AI engineers, product managers, and platform teams, it provides centralized management of 500+ models, including providers like OpenAI, Anthropic, and Google Gemini. The core value lies in reducing operational complexity: instead of juggling multiple SDKs and dashboards, users ship all traffic through one gateway that automatically logs requests and tracks metrics. This approach gives teams a single pane of glass for their entire LLM infrastructure, making it easier to scale from prototype to production without losing visibility or control. The platform has already processed over 80 trillion tokens in production, demonstrating its reliability at scale.

The primary problem Respan solves is the fragmentation that plagues modern LLM applications. Teams often integrate with multiple providers, each with separate SDKs, rate limits, and pricing models, leading to a mess of disconnected systems. When models fail or exceed quotas, engineers must manually intervene to reroute traffic, causing downtime and lost revenue. Furthermore, without unified logging, debugging becomes a nightmare of scattered logs and guesswork. This lack of centralized observability means cost overruns go unnoticed until invoices arrive, and quality regressions in user-facing features accumulate silently. Respan addresses these pain points by providing a single gateway that not only routes traffic but also captures every call in detailed traces, enabling proactive management of cost, latency, and quality.

Respan's first major feature group is intelligent routing and fallback management. With 'Stay up when models fail', users can configure fallback_models directly on requests or globally in Settings. If the primary model errors or rate-limits, the gateway automatically tries the next model in the list, retrying with exponential backoff. Additionally, load balancing across multiple API keys spreads traffic evenly to avoid hitting provider limits. The 'One API for every model' feature allows sending OpenAI-style calls to any of 500+ supported models, or passing through native SDKs while still logging every request. This eliminates the need to rewrite client code when switching providers, dramatically reducing development time and ensuring high availability without manual fallback logic.

The second major feature group is observability and monitoring. Respan provides dedicated dashboards that display requests, tokens, errors, latency, and cost in one unified view. Users can slice metrics by model or by user to identify which features or API keys are driving volume and spend. Alerting is built in: teams set thresholds for error rate, cost, latency, or token usage over a rolling window, and receive notifications via Slack, email, or webhook when limits are breached. This enables early detection of anomalies before they affect end users. Furthermore, every call is captured as a trace tree with per-span latency, and users can enrich traces with customer_identifier and metadata for deep filtering in Logs and Traces views.