Add a URL and automate outage detection, prioritization, and remediation guidance.
From detecting response changes to narrowing likely causes and preparing remediation instructions, the workflow reduces slow detection and uncertainty around what to fix first.
The difference is that it goes beyond alerts, connecting observed data to AI diagnosis and the next actions in one workflow. It reduces the need to re-explain the situation from scratch every time you open an LLM.
| Capability | External monitoring tools | General-purpose LLMs | AIOps Services |
|---|---|---|---|
| Continuous uptime and latency monitoring | ✅ | ❌ | ✅ |
| Continuous SSL and public-state monitoring | ✅ | ❌ | ✅ |
| AI-based first-pass cause estimation | ❌ | △ Requires manual prompting | ✅ Automatic |
| Prioritized remediation suggestions | ❌ | △ Possible with prompting | ✅ |
| Cross-service operational visibility | △ | ❌ | ✅ |
| Immediate remediation guidance generation | ❌ | △ Requires prompt drafting | ✅ |
Go beyond “monitoring only” or “advice only” by connecting the three phases needed for post-launch operations, with a clearer example of what the AI output actually looks like.
Continuously monitor the external state of public URLs. Track response-time changes, rendering status, and public SSL signals automatically so early warning signs are easier to catch.
It also makes “not fully down, but getting slower” situations visible early, even when it is unclear where to start investigating.
Based on degraded responses and changes in public state, the system surfaces what to check first with priority. It does not stop at alerts — it makes the next review step clearer.
Example: response time 847 ms (4.2× normal) / Priority: High / Suspected issues: slow authentication route, missing security headers.
Use the generated remediation guidance directly in your existing AI tools. Start fixing sooner without having to restate the full situation from scratch.
Pass the generated guidance into Cursor, Claude, ChatGPT, and similar tools to connect directly into your remediation workflow.
Instead of stopping at alerts, the page clarifies what changed, what to inspect first, and how to hand the context into your remediation workflow.
https://api.example.com/auth responded in 847 ms (4.2× normal baseline)
Response degradation was detected after a recent change. The output highlights the authentication route, config drift, and security-header deltas as first checks.
High — the issue may affect authentication or other critical paths, so it is ranked as an immediate review item.
From adding a URL to change detection, AI triage, and remediation actions, the flow is designed to stay low-friction.
Enter a service name and URL to start scheduled monitoring. The initial status check is available right away.
Continuously monitor latency, public-state changes, and governance shifts. When anomalies appear, AI performs first-pass triage and prioritization.
Use the generated guidance directly in your existing AI tools and development workflows. Higher plans also support API and MCP integration.
Designed for AI coders, new-business teams, and small operating teams facing different post-launch operational pain points.
Well suited for people who want to quickly catch “it works, but it is slow, unstable, or suspicious after the latest deploy” and hand off a structured starting point to AI.
For teams that do not have a dedicated operator but still need to keep first-line monitoring running after launch. It reduces missed issues and slow prioritization.
A good fit when you are operating alongside a day job or other client work and want one place for anomaly detection, prioritization, and remediation guidance.
The plan structure stays the same, with clearer guidance on which teams each tier fits. Prices are based in GBP and JPY values are approximate conversions so budget review is easier.
Prices are based in GBP. JPY values are shown only as approximate conversions. Please confirm the final charged amount in Stripe Checkout.
Our research suggests that continuous external monitoring can help surface early warning signs before major incidents and market penalties. Visit the research page for the supporting rationale and figures.
Answers to common questions.
Public HTTP/HTTPS responses, latency, page availability, and external status references for public URLs. Internal APIs and authenticated areas are not accessed.
The FREE plan currently operates around a 5-minute interval for scheduled checks. Please confirm detailed settings and future configuration flexibility based on your plan and setup.
It goes beyond notifications by connecting monitoring to AI-based first-pass triage and prioritized remediation guidance.
General-purpose LLMs are useful as advisors, but continuous monitoring, change detection, and cross-service visibility still need to be handled separately. AIOps Services covers that operational front end.
AI diagnosis is a first-pass triage layer that proposes likely causes and remediation actions with priority. Final decisions should still be made using measured data and the real production environment.
Remediation guidance is easy to pass into tools such as Cursor, Claude, and ChatGPT. Higher plans are also designed with API and MCP integration in mind.
Basic alerts are supported, and higher tiers expand access to Slack notifications and webhook integrations. Please refer to plan details for scope.
The monitoring scope focuses on public URL monitoring. It does not directly access internal APIs or authenticated areas.
No. They are approximate conversions from GBP. Please confirm the final charged amount in Stripe Checkout.
Use the “Research” menu at the top of the page, or visit /research.
Free up to 5 hosts with no credit card required. AIOps Services helps you put the first steps of post-launch operations in place: notice issues, prioritize them, and move into remediation.