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TAHO Labs logo
TAHO Labs
✓ verifiedPaid

Execution-fabric infrastructure that splits AI/compute workloads into units and packs GPUs to cut cost and raise utilization.

Zeabur logo
Zeabur
✓ verifiedFreemium

Cloud deployment platform for developers that auto-detects code and frameworks to ship apps, servers, and AI-hub services with one push.

455K visits/mo72 saves
Netify logo
Netify
✓ verifiedPaid

Local deep packet inspection and network intelligence giving businesses full visibility into application, VPN and Tor traffic.

253K visits/mo
Middleware logo
Middleware
✓ verifiedFreemium

Full-stack observability platform with an AI SRE agent that detects, debugs, and auto-fixes issues across infra, apps, and users.

47K visits/mo713 saves
Pricing

No public pricing

Free: $0/mo (1 manageable server)
Dev: $5/mo (first 14 days free, 3 servers)
Pro: $19/mo (first 14 days free, 10 servers)
Team: $79/mo (3 seats included, +$24/seat/mo)

Free trial available

No public pricing

No public pricing

Core features
  • Decomposes workloads into small routable units
  • Packs GPUs/CPUs to raise utilization
  • Works with Kubernetes, SLURM, CUDA and ROCm
  • Runs on cloud, on-prem and edge
  • Sits beneath existing orchestration with no rewrite
  • Automatic language and framework detection and deployment
  • Git-push CI/CD with zero configuration
  • Auto-scaling compute resources
  • Built-in object storage similar to S3
  • One-click managed VPS purchase
  • Unified AI Hub API for multiple AI models
  • Domain and DNS management
  • In-browser file management console
  • Local deep packet inspection agent
  • Application identification data feeds
  • VPN and Tor IP datasets
  • Network informatics and analytics
  • Developer documentation
  • 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
Use cases
  • Increasing GPU cluster utilization
  • Cutting AI/compute infrastructure cost
  • Speeding up training and inference workloads
  • Getting more from existing hardware without migration
  • Developers deploying apps without manual server config
  • Teams wanting predictable, fixed-plan hosting costs
  • Startups needing quick CI/CD pipelines
  • Projects needing bundled AI model access alongside hosting
  • Classify application traffic on a network
  • Detect VPN and Tor usage
  • Feed DPI data into security and analytics tools
  • Monitor full-stack app and infra health
  • Debug incidents faster with AI
  • Correlate frontend and backend issues
  • Observe Kubernetes and cloud environments
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