Respan | Unified AI Router, Observability & Automated Evaluations
Respan
Introduction
Respan is an enterprise-grade AI gateway, observability, and evaluation platform built specifically for production AI applications and autonomous agents. Positioned as an all-in-one control plane powering over 80 trillion tokens for teams like Retell AI, Mem0, and Gumloop, Respan unifies dynamic model routing across 1,000+ LLMs with sub-millisecond edge caching, automated fallbacks, real-time agent tracing, and continuous production evaluations (combining LLM judges, code checks, and human review).
Use Cases
High-Availability AI Routing & Outage Protection
Route requests across 1,000+ foundation models with automated fallback cascades, ensuring 99.99% uptime during third-party provider outages or rate limits.
Multi-Agent & Tool Call Tracing
Trace complex multi-turn agent runs, step-by-step tool invocations, and vector RAG context fetches into nested execution spans with granular latency and token cost breakdowns.
Continuous Production Evals & Quality Scoring
Evaluate live production spans or pre-release test datasets using composite evaluators (AI-as-a-judge, deterministic regex/code checks, and human grading queues) to detect output regressions.
Cost Reduction via Response Caching & FinOps
Cache identical or repeated prompt completions at the gateway edge and enforce granular budget/rate limits per customer, team API key, or organization.
Prompt & Model Pre-Deployment Benchmarking
Run production request samples against candidate models or revised system prompts side by side to measure win rates and performance deltas before shipping.
Features & Benefits
Universal Gateway Core
A unified, OpenAI-compatible proxy endpoint supporting 1,000+ models across OpenAI, Anthropic, Google Gemini, DeepSeek, Groq, Fireworks, and Bedrock with single-word model switching.
Automated Failover & Fallback Lists
Configurable routing cascades that automatically shift traffic to backup models or secondary inference providers upon encountering HTTP 429s, 500s, or timeouts.
Full-Stack Agent Tracing & Span Telemetry
Visualizes entire agent lifecycles—from intent classification and document embedding retrieval to generation and schema validation—down to exact input/output payloads.
Composite Evaluation Engine
Modular grading framework allowing teams to sample live production traffic (e.g., 2% of real requests) and score outputs on criteria like faithfulness, tone, and toxicity.
Edge Caching & Granular Spend Budgets
Reduces API expenses with exact-match caching while enforcing hard financial ceilings and soft alerts per workspace or external client ID.
Enterprise Governance & Compliance Certifications
Certified for SOC 2 Type II, ISO 27001, HIPAA (with BAA available), and GDPR, ensuring strict data privacy for healthcare and enterprise workloads.
Comprehensive All-in-One Convergence
Combines what typically requires 3–4 distinct tools (Portkey gateway + Langfuse tracing + Braintrust evals) into a single cohesive UI and SDK.
Battle-Tested Scale
Proven in production environments handling hundreds of millions of monthly API calls and trillions of tokens for major AI voice and agent platforms.
Zero-Friction Drop-In Integration
Seamlessly drops into existing codebases via standard OpenAI SDK base URL overrides or native Python and TypeScript/JS SDKs.
Cons
Rebranding Discovery Friction
Teams familiar with Keywords AI or older SDK imports need to align with the new Respan platform taxonomy and domain conventions.
Proxy Architecture Dependency
Adopting the full gateway routing and caching feature set requires sending outbound LLM traffic through Respan’s proxy infrastructure.
