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Full-stack observability platform with an AI SRE agent that detects, debugs, and auto-fixes issues across infra, apps, and users.
Cloud-agnostic AI/ML workflow orchestrator that runs pipelines inside a customer's own infrastructure for compute-heavy teams.
AI-powered web accessibility platform for ADA/WCAG compliance, blending automated remediation with expert services.
Agentic AI SRE using dynamic code analysis to find, root-cause, and remediate code and infrastructure issues before production.
Free cloud cost-optimization platform that pools buying power to give startups enterprise-level AWS, GCP, and Azure discounts.
No public pricing
Free trial available
Free trial available
No public pricing
- ✦Infrastructure and application performance monitoring
- ✦Log monitoring with AI insights
- ✦Real user monitoring
- ✦OpsAI SRE agent for detection and auto-fix
- ✦Synthetic and browser testing
- ✦LLM observability
- ✦Python-native dynamic workflow authoring
- ✦Automatic failure recovery, caching, and versioning
- ✦Zero Trust architecture keeping data inside customer's cloud
- ✦Real-time inference and agentic-AI workflow support
- ✦High-throughput scaling (tens of thousands of actions per run)
- ✦Local development environment matching production behavior
- ✦accessWidget automated AI remediation
- ✦accessScan accessibility auditing
- ✦accessFlow for accessible code
- ✦Screen-reader and keyboard-navigation support
- ✦Expert audits, VPAT and litigation support
- ✦CMS integrations
- ✦Dynamic Code Analysis engine
- ✦Automated root-cause analysis and remediation
- ✦Pull-request and config fix suggestions
- ✦MCP server for AI-assisted code review
- ✦Observability and data-source integrations
- ✦Runs locally or on-prem/private cloud
- ✦Automated cloud spend optimization
- ✦Group buying for enterprise discounts
- ✦Cost visibility and insights dashboards
- ✦Coverage across AWS, GCP, and Azure
- ✦No-cost service model
- →Monitor full-stack app and infra health
- →Debug incidents faster with AI
- →Correlate frontend and backend issues
- →Observe Kubernetes and cloud environments
- →ML teams orchestrating training and inference pipelines at scale
- →Biotech/geospatial companies needing GPU-heavy pipeline orchestration
- →Enterprises migrating off Airflow for ML workflow management
- →Teams requiring workflows that never send data outside their own cloud
- →Achieving ADA/WCAG compliance
- →Reducing accessibility litigation risk
- →Ongoing accessibility monitoring
- →Enterprise-scale accessibility programs
- →Reducing incident resolution time
- →Catching performance issues pre-production
- →Enhancing AI code reviews with runtime data
- →Monitoring microservice performance
- →Reducing startup cloud bills
- →Automating reserved-capacity savings
- →Gaining visibility into multi-cloud spend
- →Accessing enterprise pricing without scale