Discover AI Application Monitoring

These tools provide deep visibility into your software stack, helping you detect performance bottlenecks, track error rates, and identify server-side latency before users notice an issue. They unify fragmented logs and real-time telemetry into a single dashboard to reveal exactly where a request failed. When selecting a platform, focus on the granularity of the trace data, the ease of integrating with your existing framework, and the specific alerting filters that minimize noise during high-traffic events.

MCP Defender
MCP Defender

Automatically protects Cursor and other AI apps

OpenLIT's Zero-code LLM Observability
OpenLIT's Zero-code LLM Observability

Trace LLM requests + costs with OpenTelemetry monitoring

VoltAgent
VoltAgent

Build TS AI agents with n8n-style observability

Polylane for Vercel
Polylane for Vercel

An AI on-call engineer for your Vercel apps

BugByBug
BugByBug

AI error tracker that tells you why bugs happen and fix it.

Kubiks
Kubiks

Observability that tells you what’s wrong

Seclai
Seclai

Everything you need around your LLM calls.

Loisium
Loisium

An autonomous ecosystem for software

SnapTrace
SnapTrace

Real-time error tracking. Built for AI coders & modern apps.

Trel.to
Trel.to

Observability for web and mobile built for AI

Optics-QA
Optics-QA

One run: bug found, ticket written, fix prompt ready

Bugsly
Bugsly

AI error tracking that explains and suggests bug fixes

Progress AI Observability
Progress AI Observability

Trace, evaluate, and improve AI agents in production

EZLogs
EZLogs

Ask your product what happened, in plain english

Foglamp
Foglamp

Ship AI agents you can actually see

Currai
Currai

Observability & A/B Testing for LLM Apps

Sentinel AI
Sentinel AI

Spot Risky AI Behavior Before It Ships

AInamika
AInamika

Master the Pulse of your Business

Noryen
Noryen

Monitor, compare and catch risky AI outputs

AgentLens
AgentLens

Full observability for AI agents. Zero code changes.

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