|
Smuz — Your agents say they ran
Most agents don't fail loudly. They fail silently, keep reporting success, and nobody notices for weeks. Smuz finds those, fixes them, and leaves behind a de...
|
86 % |
|
RELAI — The continual learning engine for agents
Continual learning platform for AI agents. Turn failures and feedback into replayable environments that optimize agent performance without regressions.
|
85 % |
|
Convoy - Self-healing AI agents
Convoy learns what good and bad look like from your code and the runs you flag, watches every agent run in production, ships the fix, and validates it on rea...
|
84 % |
|
wake-u – What did your agent really get done?
wake-u shows which tasks an AI agent provably completed and how much human follow-up work was still needed.
|
84 % |
|
Mesedi | Guardians for autonomous AI agents
Observability and runtime safety for AI agents in production. Detects failures, halts runaways, and escalates the first occurrence to your team the moment it...
|
83 % |
|
Automatic Optimization Layer for AI Agents | MEGA Code
Auto-optimizes your whole agent workflow, prompts, tools, code, and orchestration, and proves every fix by execution before it ships. Model-agnostic.
|
82 % |
|
afterlives.ai - Monitor AI agents where mistakes matter
Detect and fix silent failures in agents; for high-stakes, constrained environments
|
82 % |
|
Failproof AI - End-to-End Failure Layer for AI Agents
the end-to-end failure layer for teams building ai agents. observe every run, find where agents fail, write a policy that stops it, and enforce it in realtim...
|
82 % |
|
Neens · Make every agent failure its last
Coding agents automated the build half of the lifecycle. Neens closes the half that makes sure nothing breaks twice.
|
82 % |
|
Tensiq | Reduce manipulation failures
Tensiq reduces manipulation failures. We evaluate robot policies on real hardware and measure what happens at contact, so failures stop being mysteries.
|
81 % |
|
QSI — Completion-Admission Verification for AI Agents
QSI is a fail-open checkpoint between an AI agent’s output and its next step — done, merge, tool call, payment, report, production action. It catches the fal...
|
81 % |
|
Common Sense Engine — Catch the helpful mistake before it ships
Your agent doesn't need a lecture. It needs a memory of the last time 'helpful' cost real money — checked in under 100ms, before the tool runs.
|
81 % |
|
Common Sense Engine — Catch the helpful mistake before it ships
Your agent doesn't need a lecture. It needs a memory of the last time 'helpful' cost real money — checked in under 100ms, before the tool runs.
|
81 % |
|
TraceDojo — Agent testing
Run controlled failures against your agents. Inspect every action and compare the fix.
|
81 % |
|
Gaurav Goyal — AI Reliability Consulting
I help small teams find out why their AI products fail, build the evals and tracing to catch it, and set up the monitoring so it stays fixed.
|
80 % |
|
FailEcho — Failure Intelligence for AI Agents
FailEcho is a live cross-agent failure intelligence network for AI agents and autonomous software. Agents share privacy-safe tool failures and recovery outco...
|
80 % |
|
Agnost AI | Monitoring for AI Agents
Monitor AI agents in production. Detect silent failures, understand user frustration, and approve suggested fixes.
|
80 % |
|
Eldros - Evaluate, monitor, and improve AI agents in production
Eldros is a research-backed platform that evaluates, monitors, and improves AI agents in high-stakes workflows - across voice, chat, and orchestration stacks.
|
80 % |
|
Dunetrace | Runtime reliability for AI agents
Dunetrace catches AI agent failures at runtime, alerts on Slack, finds the root cause, and fixes them. Structural and semantic detection, runtime prevention,...
|
80 % |
|
YourAgentKit — AI Agent Reliability Playbooks & Templates
Playbooks, templates, and diagnostics for people running AI agents in production. Real failure patterns. Real fixes.
|
80 % |
Detected social media networks