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SPECIFICTION
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IncidentFox vs RADCOM AIM

IncidentFox

incidentfox.ai

RADCOM AIM

radcom.com

Side by side

FigureIncidentFoxRADCOM AIM
Price from——
Free plan——
Free trialYes—
Open source——
WebYes—
Self-hostedYes—
Plans published10
Spec score · AIOps Platforms7.6 (#10)6.5 (#16)
PurposeIncidentFox is an AI-powered incident investigation agent that operates via Slack.RADCOM AIM provides AI-driven analytics for automated assurance with RADCOM ACE or legacy assurance solutions, and can enable zero-touch automation with RADCOM NWDAF.

Plans

IncidentFox

  • Free TrialFree

IncidentFox pricing →

RADCOM AIM

No plans published.

RADCOM AIM pricing →

In their own words

IncidentFox

IncidentFox is an incident investigation agent that operates through Slack, where teams can ask questions or share screenshots and files. It analyzes logs, metrics, and system data from connected observability tools, and searches Slack history for relevant discussions. Its responses can include charts, scripts, and reports in Slack threads; it also provides recommendations and can generate postmortems and documentation. The site lists 40+ integrations, including PagerDuty, AWS, Datadog, Prometheus, Grafana, GitHub, Kubernetes, Jira, and Confluence. Deployment options are hosted SaaS, on-premises or VPC, and self-hosted open core. Each investigation runs in an isolated container with a temporary filesystem. Sensitive data is redacted before it reaches the LLM, and API keys pass through a secure proxy. Write actions require human approval and include audit trails and rollback support. IncidentFox requires a Slack workspace, and installation requires a workspace administrator. Its full-feature trial is listed at free for 7 days.

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RADCOM AIM

RADCOM AIM provides AI-driven analytics for automated assurance in telecommunications networks. It works with RADCOM ACE or legacy assurance solutions and can support zero-touch automation with RADCOM NWDAF. The product detects anomalies across hundreds of KPIs and KQIs, issues early warnings, automates root-cause analysis, and supplies predictive analytics for network performance and capacity planning. After deployment, it learns baseline network behavior and creates thresholds without operator configuration. Operators can select preferred models for each use case, use internally developed AI models, and provide feedback that improves automated insights. AIM combines unsupervised and supervised machine learning, with analysis streamed in real time. RADCOM describes its products as containerized cloud-native functions supporting Kubernetes lifecycle management and public clouds including AWS, Microsoft Azure, and Rakuten Symphony. A ServiceNow partnership connects service management with service assurance and supports automated ticket resolution. Deployment is hybrid with full-stack telemetry. Pricing is available on request.

Visit radcom.com