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AmberTrace - LLM Observability for AI Agents
Detect silent failures, replay AI agent trajectories, and turn real incidents into valuable insights.
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84 % |
|
LLM Observability & Telemetry for AI Agents | telemetry.dev
Trace LLM calls and AI agents with OpenTelemetry. Inspect token usage, cost, latency, and errors with TypeScript, Python, or an existing OTLP integration.
|
83 % |
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Tapt — AI-powered issue tracking & bug reports
18 AI analyses per bug report—severity, repro steps, root cause, fixes, duplicates, and more. Structured issue tracking, Chrome extension for logs and captur...
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83 % |
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Observio | Reliable Observability for AI Applications
Observio helps teams trace AI behavior, understand model cost, catch failures quickly, and improve production systems with clarity.
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83 % |
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Lunetra — The investigation layer between support and production
Lunetra automatically investigates every support ticket against logs, traces, deployments, and code — so technical teams resolve issues with evidence, not gu...
|
82 % |
|
Middle Monitor — Unified Observability for Your Whole Stack
The unified observability platform that correlates traces, metrics, logs and errors so you find the root cause in seconds, not hours. OpenTelemetry-native.
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82 % |
|
Ceravique — live tracing for distributed systems
Observability for modern microservices. Inspect live traces, catch anomalies, and understand incidents faster.
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82 % |
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InsightRecorder — Know exactly what happened
Reconstruct production incidents from user sessions, logs, metrics and traces — with evidence your team can trust. Stop investigating across five different t...
|
81 % |
|
AI SRE and Unified Observability Platform
Replace 5+ monitoring tools with one OpenTelemetry-native platform. Reduce MTTR by 90% and costs by up to 80%. Unified APM, logs, metrics, and traces.
|
81 % |
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TraceLens
Trace, observe, and visualize AI agent runs: LLM calls, tool calls, latency, logs, and failures—explored as an interactive timeline graph.
|
81 % |
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Lggr — API logging your team can read
See requests, status codes, and latency in one place. Queue-backed logging so your API stays responsive while you debug.
|
81 % |
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ScopeCall — See every LLM call. Own your AI bill.
Open-source LLM observability without a proxy. Find the prompt, customer, model, and workflow path behind every LLM cost spike — traced from inside your app,...
|
81 % |
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Spanloom - LLM Observability for Engineering Teams
Spanloom gives engineering teams full trace visibility into LLM applications. Track spans, catch prompt drift, monitor token costs, and debug production AI p...
|
81 % |
|
TracePulse — Follow the signal
TracePulse demonstrates unified observability across logs, metrics and traces with anomaly and incident correlation.
|
81 % |
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Deeptrace
The AI SRE that never burns out
|
80 % |
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Seismark - product intelligence
From a 1-star review to the suspect commit. Correlate feedback, telemetry, and code into cited incidents.
|
80 % |
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fdbck — feedback that fixes itself
Error trackers turn a stack trace into a fix. fdbck does it for the feedback your users actually write: triage, a written plan when the work needs one, then...
|
80 % |
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AI Agent Observability & Monitoring - Latitude
Open-source AI agent monitoring platform. Full observability into what's failing in production. Discover underlying issues, get alerts when something breaks...
|
80 % |
|
TPM Spark | Find the real problem. Fix it faster.
TPM Spark helps manufacturing teams identify the production losses worth investigating and choose a practical next step.
|
80 % |
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Puse.ai — reliability monitoring for LLM apps and agents
Trace every model call: latency, tokens, cost, errors. Slack alerts on error spikes and cost regressions. One-line SDK, self-hostable.
|
80 % |
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