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Agentic AI platform ('Aiden') that automates incident response, infrastructure-as-code and observability tasks with policy-based governance.
AI-powered visual and functional test-automation platform for cross-browser, component, and accessibility testing.
Automated AWS usage optimization platform giving engineers 150+ recommendations across 50+ services, averaging ~10% savings.
No-code chatbot builder that trains an AI assistant on business data for support, sales, and lead capture across web and messaging apps.
No public pricing
No public pricing
No public pricing
Free trial available
Free trial available
Free trial available
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
- ✦Automated service discovery and dependency topology mapping
- ✦SLO-based alert triage and prioritization
- ✦AI-driven root cause analysis with pre-built workflows
- ✦Human-approved remediation with full audit trails
- ✦Works alongside existing tools like Datadog, Grafana, New Relic
- ✦Governance and policy enforcement layer for agent actions
- ✦Visual AI UI validation
- ✦Cross-browser and cross-device testing
- ✦Component and accessibility testing
- ✦Codeless recorder and NLP test builder
- ✦Test orchestration and self-healing tests
- ✦Root-cause analysis and automated maintenance
- ✦150+ recommendations across 50+ AWS services
- ✦Zombie and unused resource cleanup
- ✦Over-provisioned rightsizing
- ✦Idle-resource scheduler
- ✦SpotBot for ECS Fargate spot/on-demand switching
- ✦AWS console extension with Slack/Teams alerts
- ✦Train chatbot on uploaded documents, website pages, and live data sources
- ✦Embed widget on any website
- ✦Deploy across WhatsApp, Messenger, and Slack
- ✦Live agent takeover with chat summaries
- ✦Custom bot persona and brand voice
- ✦API-based tools for real-time data lookups
- ✦Meeting/appointment booking automation
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →SRE teams reducing mean-time-to-resolution during incidents
- →Platform engineers wanting policy-governed AI infrastructure management
- →Enterprises needing SOC 2 / PCI / HIPAA-compliant AI operations
- →Catch visual UI regressions
- →Automate cross-browser testing
- →Scale QA across large test suites
- →Run accessibility checks
- →Cutting AWS spend automatically
- →Rightsizing over-provisioned resources
- →Scheduling idle resources off-hours
- →Giving DevOps in-console cost recommendations
- →Automating 24/7 customer support replies
- →Answering pre-sale questions to boost conversions
- →Collecting leads and scheduling meetings
- →Summarizing chats for human agent handoff
- →Building an internal knowledge assistant for staff