We detected 1,386 customers using Incident.io and 19 companies that churned or ended their trial. The most common industry is Software Development (37%) and the most common company size is 51-200 employees (37%). Our methodology involves discovering URLs with known URL patterns through web crawling, certificate transparency logs, or modifications to subprocessor lists.
About Incident.io
Incident.io provides an all-in-one incident management platform that unifies on-call scheduling, real-time incident response, and status pages to help engineering teams resolve software outages faster. Powered by AI and integrated with Slack and Microsoft Teams, it automates workflows and coordinates communication throughout the entire incident lifecycle from alert to resolution.
📊 Who in an organization decides to buy or use Incident.io?
Source: Analysis of 100 job postings that mention Incident.io
Job titles that mention Incident.io
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Based on an analysis of job titles from postings that mention Incident.io.
Job Title
Share
Site Reliability Engineer (SRE)
23%
Backend Engineer
16%
Incident Manager
13%
Manager, IT Support
6%
My analysis shows that Incident.io buyers span technical leadership and operations roles. While only 2 of 70 postings are formal leadership positions, the purchasing decision-makers appear to be Directors of Engineering, Platform Engineering Managers, and Heads of Site Reliability. These leaders are hiring heavily for SREs (23%), backend engineers (16%), and dedicated incident managers (13%), signaling strategic priorities around operational excellence, platform reliability, and scaling incident response capabilities as companies grow.
Day-to-day users are predominantly engineers and technical operators. SREs use Incident.io to coordinate responses, manage on-call rotations, and drive post-mortems. Backend and platform engineers integrate it into their observability stack alongside tools like Datadog, PagerDuty, and Slack. Incident managers leverage it to orchestrate cross-functional response, track SLAs, and run retrospectives. Multiple postings mention using Incident.io for alerting workflows, runbook management, and blameless postmortem processes.
The recurring pain points center on scaling reliability practices and reducing toil. Companies want to "minimize business impact" and "reduce the likelihood of major incidents" while maintaining rapid product velocity. One posting emphasizes building "a proactive, agile approach to incident response" with AI-driven insights. Another seeks to "establish clear escalation paths and backup coverage to drive 24/7 operational readiness." A third highlights the need to "drive accountability" and ensure "incidents are resolved promptly and root causes are addressed comprehensively." These phrases reveal organizations struggling to professionalize incident management as they scale.
🔧 What other technologies do Incident.io customers also use?
Source: Analysis of tech stacks from 1,386 companies that use Incident.io
Commonly Paired Technologies
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Shows how much more likely Incident.io customers are to use each tool compared to the general population. For example, 287x means customers are 287 times more likely to use that tool.
I noticed that Incident.io users are fundamentally engineering-first companies building modern software products. The extremely high correlation with Docker Hub, Linear, and PagerDuty tells me these are teams shipping code continuously who need robust incident management because downtime directly impacts their business. They're not using incident management as a compliance checkbox. They're using it because reliable operations are core to their value proposition.
The pairing with Ashby is particularly revealing. This recruitment platform is popular with high-growth startups that are scaling their technical teams quickly. Combined with Linear for project management and GoLinks for internal knowledge sharing, I see companies that are intentionally building strong engineering cultures. They're investing in tools that reduce friction and improve collaboration, not just checking feature boxes. The PagerDuty correlation reinforces this since they're clearly running 24/7 services that require on-call rotations and automated alerting alongside incident management.
My analysis shows these are product-led growth companies, likely Series A through C, in the 50 to 500 employee range. They're past the scrappy startup phase where engineers accept using disparate tools, but they're not yet large enterprises bogged down by procurement processes. The presence of Linear instead of Jira is telling. These companies prioritize developer experience and modern workflows. They're likely SaaS businesses or infrastructure companies where uptime and incident response directly tie to customer trust and revenue.
👥 What types of companies is most likely to use Incident.io?
Source: Analysis of Linkedin bios of 1,386 companies that use Incident.io
Company Characteristics
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Shows how much more likely Incident.io customers are to have each trait compared to all companies. For example, 2.0x means customers are twice as likely to have that characteristic.
Trait
Likelihood
Funding Stage: Series B
118.5x
Funding Stage: Series A
55.8x
Industry: Computer and Network Security
17.5x
Funding Stage: Seed
14.6x
Industry: Software Development
9.8x
Industry: Technology, Information and Internet
6.6x
I noticed that Incident.io's customers are predominantly technology companies building complex, mission-critical systems where downtime has real consequences. These aren't simple websites. They're companies operating infrastructure that processes billions of transactions (AppCard mentions "% of item-level transaction data"), manages trillions in assets (FundApps monitors "$30 trillion in assets"), or powers critical services for millions of users. Many are B2B SaaS platforms, fintech companies, cybersecurity firms, and digital infrastructure providers. There's also a significant presence of companies in highly regulated industries like financial services, healthcare technology, and enterprise software.
These companies span the full spectrum from early-stage to enterprise, but there's a concentration in the growth stage. I see many Series A through Series C companies (Zen Educate at Series B with $37M, Torq at Series C with $70M, Noma Security at Series B with $100M). There are also established enterprises like MongoDB, Docusign, and Entain alongside smaller but funded startups. The employee counts cluster around 50-200 people, suggesting companies past the scrappy startup phase but still scaling rapidly.
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