# incident.io vs Squadcast: which do AI models recommend for incidents, October 2026

IT AI Recommendation Index, October 2026 Edition, Incident management and on-call. Six of fourteen models named incident.io first on the direct prompt; zero named Squadcast. Page: https://it-ai-index.com/operations/incident-management-and-on-call/incident-io-vs-squadcast/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| incident.io | 32% | #1 of 11 | 5% | 57 | 14 of 14 |
| Squadcast | 8% | #4 of 11 | 4% | 25 | 12 of 14 |

## The direct prompt, model by model

- GPT-5.4 mini: incident.io first (first choices: incident.io) (alternatives: PagerDuty, Rootly)
- Gemini 3.5 Flash: incident.io first (first choices: incident.io) (alternatives: FireHydrant, Freshservice, Rootly)
- DeepSeek V4 Flash: incident.io first (first choices: incident.io) (alternatives: Freshservice, Jira Service Management)
- Kimi K2: incident.io first (first choices: incident.io) (alternatives: Squadcast)
- GLM 4.7 FlashX: incident.io first (first choices: Rootly, incident.io) (alternatives: Jira Service Management, PagerDuty)
- GPT-6 Luna: incident.io first (first choices: incident.io) (alternatives: PagerDuty, Rootly)
- Claude Haiku 4.5: neither first, one named (first choices: Freshservice) (alternatives: HaloITSM, Hyperping, ManageEngine ServiceDesk Plus, Rootly, Zenduty, ilert, incident.io)
- Perplexity Sonar: neither first, one named (first choices: Freshservice) (alternatives: PagerDuty, Rootly, incident.io)
- Grok 4.20: neither first, one named (first choices: Freshservice) (alternatives: InvGate Service Management, Jira Service Management, ManageEngine ServiceDesk Plus, PagerDuty, incident.io)
- MiniMax M2.5: neither first, one named (first choices: Freshservice, PagerDuty) (alternatives: Jira Service Management, incident.io)
- Muse Glimmer 30B: neither first, one named (first choices: Freshservice) (alternatives: PagerDuty, Rootly, incident.io)
- Mistral Small: neither named (first choices: Freshservice, PagerDuty) (alternatives: ManageEngine ServiceDesk Plus)
- Llama 4 Maverick: neither named
- Qwen 3.7 Flash: neither named (first choices: PagerDuty) (alternatives: Datadog Incident Management, FireHydrant, Opsgenie)

## What the models said about incident.io

- "missing features in incident.io, particularly in reporting capabilities and SLA tracking" (Claude Haiku 4.5, negative prompt, soft negative)
- "if your teams don't want incident workflows tied to Slack or Microsoft Teams" (GPT-6 Luna, negative prompt, soft negative)
- "Pricing surprises: Costs spike sharply after small-team thresholds" (Qwen 3.7 Flash, negative prompt, soft negative)
- "Small team ≤5-10 responders and wants zero cost: incident.io free, FireHydrant free up to 10 responders, Better Stack free, or Opsgenie free up to 5 users." (Muse Glimmer 30B, budget prompt, first choice)
- "Choose incident.io if your team is Slack-centric and values speed of implementation, modern UX, and transparent all-in-one pricing." (Kimi K2, direct prompt, first choice)
- "Highly recommended for mid-market/scale-up companies. It is highly polished, opinionated, runs seamlessly inside Slack/Teams" (Gemini 3.5 Flash, scale prompt, first choice)

## What the models said about Squadcast

- "Squadcast (now SolarWinds) — Be cautious" (DeepSeek V4 Flash, negative prompt, soft negative)
- "Squadcast is the cheapest credible option, with a free tier up to 5 users and Pro at $12/user/mo" (Claude Haiku 4.5, budget prompt, first choice)
- "The best incident management platform for a company with a limited budget is Squadcast" (Llama 4 Maverick, budget prompt, first choice)
- "I'd recommend starting with Squadcast (if you have under 5 team members)" (MiniMax M2.5, budget prompt, first choice)

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category. Comparisons are drawn for the top eight products in each category. Published under CC BY 4.0; the output is the models' output, and nothing here is a recommendation by the index.