Observyze
Overview
Observability and runtime control for production AI agents, with tracing, cost monitoring, guardrails, budgets and circuit breakers.
Observyze is an AI-agent observability and runtime-control platform for teams running production LLM applications. It provides tracing for supported prompts, tool calls and model responses, monitors cost and latency, and can enforce configured runtime policies through SDK or proxy-based capture. Its proxy gateway can apply pre-dispatch controls such as prompt-injection blocking, execution budgets and circuit breakers, while asynchronous output evaluations record hallucination and safety signals for investigation and later policy decisions.
AI Agent Store research
What the evidence says about Observyze
Observyze combines production AI-agent tracing with active runtime controls. The distinctive angle is that it is not limited to post-hoc observability: teams can instrument through an SDK or route traffic through a proxy gateway to enforce configured policies, budgets and circuit breakers before supported provider requests are dispatched.
Verified October 10, 2026
Verified capabilities
- High-fidelity tracing
Captures supported prompt, tool-call and model-response boundaries in a searchable trace timeline for debugging agentic chains.[1]
- Cost and latency monitoring
Monitors LLM cost and latency and supports per-trace cost attribution for production AI traffic.[1]
- SDK and proxy capture options
Teams can instrument in-process with a lightweight SDK or route supported OpenAI-compatible traffic through the Observyze proxy gateway.[1]
- Runtime policies and circuit breakers
Supports configured execution budgets, runtime policies and persisted circuit state that can stop subsequent proxy requests after thresholds are crossed.[1]
- Pre-dispatch input guardrails
The proxy can reject configured prompt-injection patterns before a supported request reaches the provider.[1]
- Asynchronous output evaluation
Records hallucination and safety signals for investigation and later policy decisions after responses complete.[1]
- Redaction layers
The official page lists local and server redaction layers as part of its capture and control architecture.[1]
- Stack compatibility
The page lists native support for OpenAI, Anthropic and Gemini, tested endpoints for Groq, Mistral, Cohere and Ollama, and compatibility mentions for LangChain, Vercel AI SDK and Next.js.[1]
Where it fits best
- Engineering teams operating production AI agents that need request-scoped tracing across prompts, tool calls and model responses.[1]
- Teams that want to monitor LLM cost and latency per trace and investigate expensive or failed agent behavior.[1]
- Teams that need configured runtime policies, execution budgets and circuit breakers to reduce the risk of runaway agent loops or unsafe requests.[1]
Buying and deployment notes
Observyze is advertised as free during Early Access for 90 days with no credit card required. No public starting price is provided in the supplied context.[1]
Platforms: Web product, Python SDK integration, TypeScript SDK integration, OpenAI-compatible proxy, cURL/API usage, OpenAI, Anthropic, Gemini, LangChain, Vercel AI SDK, Next.js[1]
Deployment: Hosted Observyze proxy gateway, In-process lightweight SDK[1]
Important considerations
- The official page describes Observyze as Early Access with 90 days free, so buyers should verify post–Early Access pricing and commercial terms before relying on it for a long-term production budget.[1]
- Provider coverage should be checked against the listed support: the page names native support for OpenAI, Anthropic and Gemini, with tested endpoints for Groq, Mistral, Cohere and Ollama.[1]
- Output evaluations are described as asynchronous; they explain completed responses and can influence subsequent handling, rather than necessarily blocking the already completed response.[1]
- The page notes that budget-driven circuit behavior and savings depend on request cost, state-store availability and configured thresholds.[1]
Sources and research method (1)
We record only claims tied to public sources checked by our team or listing workflow. Counts above are derived directly from this profile, not a subjective rating.
- AI Agent Observability & Runtime Control | ObservyzeOfficial site · checked 2026-10-10
Autonomy level
38/100
Our subjective rating of how independently the product carries out its documented tasks, considering the human setup, input, approval and review it needs. This is not a measured success rate.
Comparisons
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Some of the use cases of Observyze:
- Tracing production LLM and agent workflows
- Monitoring AI agent cost, latency and failures
- Enforcing configured runtime budgets and circuit breakers
- Investigating hallucination and safety signals
- Adding observability through an SDK or proxy gateway
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