Zespan - AI Agent Reliability Platform
Zespan gives engineering teams full observability into AI agents running in production. When an agent produces wrong output, costs spike, or a multi-agent workflow fails, Zespan shows exactly what happened, which tool call failed, which prompt caused the regression, which model was called, and what it cost.
Distributed Tracing
Every agent run is captured as a agentic trace, LLM calls, tool invocations, agent handoffs, and retrieval steps as linked spans with latency and token counts. Multi-agent workflows appear as a single unified trace, not N disconnected events.
Cost Attribution
Exact USD spend per agent, model, prompt version, and user session. Know which agents are expensive before your bill arrives.
Evaluations
Run LLM-as-judge evaluations on every trace automatically. 12 built-in templates cover faithfulness, relevance, toxicity, and task completion. Catch quality regressions before users do.
Prompt Management
Version, compare, and A/B test prompts in production. Deploy prompt changes with a confidence score backed by eval results.
Guardrails
Block toxic, off-topic, or policy-violating outputs before they reach users. Pre- and post-generation checks with configurable fail modes.
ZespanPilot
Chat with your traces. Ask "which agent had the highest error rate this week?" or "show me all runs where cost exceeded $1" in plain language.
Integrations
Works with OpenAI, Anthropic, Google Gemini, AWS Bedrock, Groq, Mistral, OpenRouter, LiteLLM, LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex, Vercel AI SDK, Google ADK, Haystack, and Semantic Kernel. Two lines to instrument. OpenTelemetry native.
