# Alert & Incident Triage: done-for-you AI automation by BufferSol

> A done-for-you alert and incident triage automation is an AI agent that sits between your monitoring tools and your on-call team. It reads alerts from Datadog, Azure Monitor, your RMM or SIEM, groups duplicates, checks recent changes and known issues, runs pre-approved diagnostic steps, and decides whether to suppress, ticket or page. When it pages, the engineer gets a short summary with evidence. BufferSol builds and tunes it with your team and logs every decision.

- Canonical: https://buffersoltech.com/done-for-you/automations/incident-triage
- Industries: SaaS & Technology (MSPs & IT services)
- Provider: BufferSol Technologies (New York; serving the US, UK, Ireland, Canada and the EU)
- Timeline: live in 3 to 6 weeks
- Pricing: quoted after a short scoping call

## Every alert read, grouped and routed, so on-call engineers only wake for real incidents

**Who it is for:** Internal IT and operations teams, SaaS companies and MSPs whose monitoring produces hundreds of alerts a day, where technicians have started ignoring alerts and real incidents get noticed late.

### Signs you need it
- Technicians mute alert channels or set email rules to hide them.
- The same alert fires many times a day and clears itself.
- A real outage was found by a customer before monitoring caught it.
- Every new tool added more alerts and nobody tuned them.
- On-call engineers are woken for issues that could wait until morning.

## Business outcomes
- **Fewer, better pages.** Duplicates and self-clearing alerts are grouped or held, so the alerts that reach a person are worth their attention.
- **Faster start on real incidents.** Each page arrives with affected systems, recent changes, related alerts and diagnostic results, so the engineer starts fixing instead of gathering context.
- **A clear picture of alert noise.** Weekly reports show which monitors are noisy, which thresholds to change and which clients or services generate the most work.

## How it works today
1. Monitoring tools, the RMM and cloud consoles each send alerts to email, Teams and the PSA or ITSM board.
2. A technician scans the stream, opens what looks serious and ignores familiar noise.
3. For a real issue, they log into several consoles to check what changed and who is affected.
4. On-call is paged for anything above a severity threshold, day or night.
5. Tickets are created by hand, often after the issue is fixed, with little detail.
6. Thresholds stay at default because nobody has time to tune them.

Hidden costs:
- Alert fatigue: real incidents get missed among routine alerts.
- Burned-out on-call engineers and technicians who leave.
- Slower response that customers and clients notice, and that shows up at renewal.

## How it works done for you
1. BufferSol connects your alert sources (Datadog, Azure Monitor, CloudWatch, Prometheus, NinjaOne, ConnectWise RMM or your SIEM) to the agent, and imports your service map and on-call schedules.
2. For each alert, the agent groups duplicates and related signals into one candidate incident and checks recent deployments, change tickets and maintenance windows.
3. It runs read-only diagnostic steps you approve, such as checking service health, disk usage or recent logs, and attaches the results.
4. Using rules written with your team, it decides to hold a self-clearing alert, open a ticket for business hours, or page on-call now. A person can override any decision.
5. When it pages through PagerDuty or Opsgenie, the message includes a short summary, the evidence, likely cause and the runbook link.
6. Remediation beyond diagnostics, such as restarting a service, only runs if it is on the approved list for that system, or after the engineer confirms.
7. Every grouping, decision and action is logged, and a weekly noise report lists monitors to tune or retire.

## What changes for the team
- **On-call engineer.** Today: Is paged for noise at night and spends the first part of each incident collecting context. Done for you: Gets fewer pages, each with a summary, evidence and runbook, and confirms fixes.
- **NOC or MSP technician.** Today: Watches a stream of alerts across many clients and decides by instinct what matters. Done for you: Works a ranked queue of grouped incidents and tunes noisy monitors from the weekly report.
- **IT or operations manager.** Today: Has little data on alert volume, noise or response times by service or client. Done for you: Reviews noise and response trends and decides where to invest in fixes.

## KPIs we measure
- **Pages per on-call shift:** Count of human pages per shift, baselined from PagerDuty or Opsgenie history.
- **Alerts to incidents ratio:** How many raw alerts collapse into each actionable incident, tracked weekly.
- **Mean time to acknowledge and resolve:** From the first related alert to acknowledgement and resolution, by severity.
- **Missed incidents:** Incidents first reported by users or clients rather than monitoring, reviewed monthly.
- **Override rate:** How often engineers change the agent's hold, ticket or page decision, used to tune rules.

## Industry data
- 19%: year-over-year growth in critical incidents from 2019 to 2020 (PagerDuty State of Digital Operations, 2021) ([PagerDuty](https://www.pagerduty.com/newsroom/pagerduty-state-of-digital-operations-report-underscores-business-and-human-costs-of-pandemic/))
- 9% more: off-hour interruptions (6PM-10PM) experienced by responders (PagerDuty State of Digital Operations, 2021) ([PagerDuty](https://www.pagerduty.com/newsroom/pagerduty-state-of-digital-operations-report-underscores-business-and-human-costs-of-pandemic/))

## Systems it connects to
PagerDuty, Opsgenie, Datadog, Azure Monitor, Amazon CloudWatch, NinjaOne, ConnectWise, ServiceNow, Jira Service Management, Microsoft Sentinel

## Guardrails
- Critical alerts on systems you name always page a person, whatever the agent thinks.
- Diagnostic steps are read-only; any remediation runs only from an approved list or after an engineer confirms.
- Held or suppressed alerts are kept and reviewed in the weekly report, never silently dropped.
- The agent uses least-privilege credentials per system and client, stored in your secrets manager.
- Every grouping, decision, page and action is logged with the evidence used.

## What teams say about this work
- When technicians face hundreds of alerts a day they build shortcuts and critical alerts get missed, and every new tool adds its own noise until serious issues look like routine ones. ([Liongard](https://www.liongard.com/blog/alert-fatigue-msp-client-retention))
- RMM alerts fire on conditions that clear themselves, sometimes many times a day, and blanket policies across clients flood the queue until technicians stop trusting alerts at all. ([MSP+](https://mspplus.com/blog/feeling-burned-by-bad-alerting-trust-your-rmm-alerts-again-with-this-simple-guide))
- Incident tool users say alerting often triggers too many notifications from false alerts, and that messy monitoring inputs can still overwhelm people with pages. ([G2](https://www.g2.com/products/pagerduty/reviews_and_filters))
- Adding headcount to sort through noise doesn't reduce it; MSP operators argue correlation, deduplication and context before a ticket is the real fix. ([8West IT](https://8westit.com/blog/posts/alert-fatigue-is-not-a-staffing-problem-it-is-a-tooling-problem/))

## Delivery: live in 3 to 6 weeks
1. Week 1: discovery, access and a baseline of today's numbers.
2. Weeks 2–3: build the agents and connect your systems, with your rules and approvals.
3. Weeks 3–5: test on your real history, then pilot on live work with your team reviewing.
4. Weeks 4–6: staged go-live, training, dashboards and handover.

## Executive Ask questions for this workflow
- How many times was on-call paged last month, and how many of those were real incidents?
- Which services or clients generate the most alert noise, and what would fix it?
- Were any incidents last quarter reported by customers before our monitoring caught them?

## Frequently asked questions
### Could the agent hide a real incident?
We design against that. Systems and alert types you name as critical always page a person. Held alerts are never deleted; they stay visible and appear in the weekly report. The agent starts in shadow mode, where it records what it would have done while your normal paging continues, so you can compare its decisions with real outcomes before it routes anything.

### Will it make changes to our systems?
Only what you approve. By default the agent runs read-only diagnostics such as health checks, log queries and disk usage. Remediation steps, like restarting a service or clearing a queue, are added one at a time to an approved list per system, and anything outside that list waits for an engineer to confirm. Every action is logged with its result.

### Does it work for MSPs with many client environments?
Yes. We connect your RMM and PSA, such as NinjaOne, ConnectWise or Datto with Autotask, and keep each client's rules, credentials and reports separate. Technicians see one ranked queue across clients, and each client can get its own monthly summary of incidents and noise, which is useful in business reviews.

### How long does it take to go live?
Plan on 3 to 6 weeks. We review a recent sample of alerts with your team, connect alert sources, service maps and on-call tools, and write the routing rules together. The agent then runs in shadow mode while engineers compare its calls with their own. Once the override rate is acceptable, it starts routing, beginning with the noisiest sources.

### What does it cost?
Pricing is quoted after a short scoping call. It depends on alert volume, how many monitoring and on-call tools we connect, the number of client environments for MSPs, and how many remediation steps you want automated. You receive a written fixed-scope quote before any build starts, so the cost is agreed before we touch your systems.