20 Signals

AgentOps Incident Triage Console

A SaaS observability tool that monitors AI agents, detects failures, and speeds incident triage with evaluation traces and operational context.

Added Jun 11, 2026

Last signal 1w ago

Job Ads

AI Observability

Incident Management

DevOps

Opportunity Score

Opportunity: Medium (61%)

Evidence Strength

Vol: 50%

Urg: 50%

Spec: 100%

Market Analysis

high

$ high

Multi-billion dollar observability and AIOps market, with a growing AI/ML observability segment driven by production generative AI adoption

The Problem

Teams building AI agents and generative AI applications struggle to monitor, troubleshoot, and optimize systems once they move from prototype to production. Existing observability workflows are being stretched by agent behavior, model outputs, fraud and integrity risks, and incident response needs across engineering and operations teams.

Potential Solution

The product provides a unified workspace for AI agent traces, evaluations, runtime monitoring, and incident triage. It connects observability data with AI-assisted detection, root-cause hints, and investigation workflows so teams can identify degraded behavior, failed tool calls, suspicious usage, or customer-impacting incidents faster.

Why Now?

Generative AI systems are moving into production, and multiple companies are hiring specifically around AI observability, ML observability, AI-native incident management, and AI-assisted investigations. This suggests demand is shifting from experimentation toward operational reliability tooling.

Market validation

Opportunity score

82% score confidence

Search demand

Trend snapshot pending

Competition (0)

No matched competitors yet

Showing 1-20 of 20 signals

Senior Manager, Software Engineering - DevOps, Observability & Monitoring

cvs-healthJul 19, 2026

AIOps & Intelligent Operations: Drive the adoption of AIOps solutions for predictive monitoring, anomaly detection, and automated root cause analysis. Integrate machine learning models and analytics into monitoring pipelines to proactively detect and prevent incidents.

embedding

Lead Software Engineer

jpmorgan-chase-bank-n-a-s74fc2367eJul 14, 2026

• Build AI-assisted observability and operations use cases (anomaly detection, alert correlation, incident prediction, runbook automation, GenAI-assisted triage).

embedding

Sr. SRE AI Engineer

navanJul 7, 2026

Improve observability. Build dashboards, alerts, traces, logs, and runbooks that make service health clear, actionable, and tied to SLOs and customer impact. Apply AI to SRE workflows. Prototype and productionize AI-assisted systems that create effective and efficient operations

embedding

Data & AI Operations Engineer

singapore-telecommunications-limited-199201624dJul 1, 2026

Operationalise successful AI use cases into reliable, scalable, and maintainable production capabilities Improve system observability, incident detection, root-cause analysis, and operational efficiency through automation and intelligence

embedding

Data & AI Operations Engineer

singapore-telecommunications-limited-199201624dJul 1, 2026

Improve system observability, incident detection, root-cause analysis, and operational efficiency through automation and intelligence Support the end-to-end lifecycle of AIOps, MLOps, and LLMOps solutions, from experimentation to production

+17 more signals