The startup offers an AIOps platform that automates repetitive business and operations processes, providing enterprise-grade tools for building, deploying, and managing cloud-native applications. This platform enables clients to enhance operational efficiency and achieve specific business outcomes through rapid application development with language-specific SDKs.
Funding
$24.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Modern IT environments generate vast amounts of operational data from disparate sources, creating data silos and hindering comprehensive visibility. Traditional AIOps solutions struggle to effectively ingest, process, and correlate this diverse data, leading to delayed incident resolution and missed opportunities for proactive optimization.
Solution
CloudFabrix offers a robotic data automation platform that unifies network observability, AIOps, and automation. The platform uses AI/ML to reduce alert noise, accelerate incident resolution through root cause analysis, and provide predictive insights to prevent outages. Its robotic data automation fabric (RDAF) acts as a low-code streaming analytics platform for all MELT (metrics, events, logs, and traces) and operational data. CloudFabrix enables composable analytics, allowing users to create tailored analytics solutions based on their specific needs and extract actionable insights.
Target Audience
CloudFabrix targets IT Planning/IT Leaders, AIOps/ITOps/NOCOps, NetworkOps, and PlatformOps/DevSecOps professionals seeking to improve operational efficiency and business outcomes through data-driven automation.
Features
- Robotic Data Automation Fabric (RDAF) for low-code streaming analytics and data automation
- Unified Network Observability and Automation for AI-driven end-to-end network operations
- Composable Analytics for creating custom dashboards and analytics
- Macaw AgenticAI Co-pilot for AIOps and Observability, leveraging Generative AI
- Observability Pipelines for ensuring the health and performance of data systems
- Full-stack service mapping for comprehensive visibility across hybrid cloud environments
- Bot-based architecture for streamlined data automation and management