Monitor your AI agents in production
Catch and handle agent loops before they reach your users.
One platform to catch and improve agent behavior
Catch silent failures that impact users
Detect beyond basic failure modes in real-time. Customize modes based on your agent's goals and align closer to delivering user value.
Mode 1
User rephrases the agent multiple times, indicating dissatisfaction.
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Mode 2
Agent makes a choice without referencing available evidence or goals.
Custom modes in plain English
- Failed tool calls
- User frustration in sessions
- Agent looping
- Information misrepresentation
Root-cause on autopilot
Analyze, triage, and track issues in one continuous flow.
Autopilot Analysis
Pull in context from code, logs, and prompts
Every issue gets automatically analyzed with runtime context from code, ticketing, traces, and prompts to pinpoint the root-cause.
Code
41 def summarize_deal_flow(
42 self, date_range):
43 range = fallback(90)
44 return self.query(range)
Traces
__start__
▸ retrieve_deals 0.3s
▸ summarize_deal_flow 1.2s
▸ format_output 0.4s
__end__
Prompts
Summarize pipeline deals
for the given date range.
No mention of actual_range_used
Root-cause identified
summarize_deal_flow silently overrides date_range to "last 90 days" via probabilistic fallback. System prompt does not instruct agent to use actual_range_used.
Cross-reference check
5 issues → 3 high-signal3 high-signal issues cross-referenced across patterns. 2 filtered as noise
High-Signal Triage
Surface only issues that matter
Issues are cross-referenced across patterns so only high-signal ones get surfaced.
Performance Tracking
Track failure modes and agent performance over time
Track which failure modes fire most and how the agent trajectories are responding for each custom mode
Agent trajectories
Tool hallucination
Extended date range
Skips confirmation
Failure mode frequency
Tool hallucination
built-in23
18% of all issues
Extended date range
custom41
32% of all issues
Skips confirmation
custom15
12% of all issues
Fix failures fast
Operate with complete context and ship solutions faster before more users get impacted
#nexus-alerts
Tool hallucination detected
checkout-agent · just now
Prompt v4.2 removed inventory fallback on line 14
View in Nexus →Slack Alerts
Get notified the moment a silent failure is detected, straight to the right channel with full context.
NEX-247Tool hallucination in checkout flow
Linear Tickets
Auto-create tickets with root-cause analysis, logs, and reproduction steps so your team can act immediately.
Nexus MCP
Plug Nexus MCP into Claude Code or Cursor and jump straight into fixing with full issue context loaded without needing to do additional investigation
fix: tool selection fallbackAuto-generated by Nexus · ready to merge
Automated PRs
Ship code fixes automatically. Nexus drafts pull requests with the changes needed to resolve the issue.
Connect with tools you already use
Don't have observability?
Just use Nexus.
pip install nexus-library