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Vibe-coding builder creating full-stack apps by chatting with AI.
Automated AWS usage optimization platform giving engineers 150+ recommendations across 50+ services, averaging ~10% savings.
No-code platform for building and running AI agents that automate work across data, sales and support tasks.
AI prototyping tool that generates UI matching your design system, letting product teams test features fast.
Cloud-agnostic AI/ML workflow orchestrator that runs pipelines inside a customer's own infrastructure for compute-heavy teams.
Free trial available
No public pricing
- ✦CodeFlying enables full-stack app creation via chat in minutes
- ✦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
- ✦Visual canvas to orchestrate multi-agent workflows
- ✦Prebuilt specialized agents (data, support, CRM, sales)
- ✦Access to many AI models with no vendor lock-in
- ✦Slack, Teams and email agent interaction
- ✦Recurring/scheduled tasks and triggers
- ✦Enterprise security: RBAC, VPC, audit logs, spend controls
- ✦AI UI generation from prompts
- ✦Match existing styling and design systems
- ✦Rapid, high-fidelity prototyping
- ✦Live team editing and sharing
- ✦Enterprise security and compliance
- ✦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
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- →Cutting AWS spend automatically
- →Rightsizing over-provisioned resources
- →Scheduling idle resources off-hours
- →Giving DevOps in-console cost recommendations
- →Automate data analysis and reporting
- →Triage support tickets and spot patterns
- →Keep a CRM updated and research prospects
- →Deploy AI agents across a team's tools
- →Prototype new product features
- →Test designs with customers
- →Build design-system-consistent mockups
- →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