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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.

Pump logo
Pump
✓ verifiedFree

Free cloud cost-optimization platform that pools buying power to give startups enterprise-level AWS, GCP, and Azure discounts.

64K visits/mo3.2K saves
Releem logo
Releem
✓ verifiedFree trial

Continuously analyzes MySQL, MariaDB, and PostgreSQL workloads to recommend and safely apply configuration and query fixes.

22K visits/mo5.1K saves
AquilaX logo
AquilaX
✓ verifiedFreemium

AI DevSecOps platform running 32 parallel scanners with an AI engine that cuts false positives and auto-generates fix PRs.

14K visits/mo
Pricing

No public pricing

No public pricing

Starter: $39/month billed annually (1 database server, or $49/month on-demand)
Scale: $123/month billed annually (up to 5 database servers, or $199/month on-demand)
Hosting: $99/month (up to 9 database servers)

Free trial available

Free: $0/mo
Premium: $19/mo
Ultimate: $99/mo (14-day trial)

Free trial available

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
  • Automated cloud spend optimization
  • Group buying for enterprise discounts
  • Cost visibility and insights dashboards
  • Coverage across AWS, GCP, and Azure
  • No-cost service model
  • Workload-based configuration tuning
  • SQL query analytics and optimization suggestions
  • Schema optimization (duplicate/unused index detection)
  • 24/7 automated health and security monitoring
  • One-command agent installation
  • Human approval required before applying changes
  • 32 scanners (SAST, SCA, DAST, IaC, secrets, container)
  • Securitron AI false-positive filtering
  • AI auto-remediation with fix PRs
  • ASPM and CSPM posture management
  • CI/CD, IDE and MCP integrations
  • On-premises deployment option
Use cases
  • Increasing GPU cluster utilization
  • Cutting AI/compute infrastructure cost
  • Speeding up training and inference workloads
  • Getting more from existing hardware without migration
  • Reducing startup cloud bills
  • Automating reserved-capacity savings
  • Gaining visibility into multi-cloud spend
  • Accessing enterprise pricing without scale
  • Database teams reducing manual tuning workload
  • Hosting providers optimizing customer databases at scale
  • Engineering teams without a dedicated DBA fixing performance issues
  • AWS RDS users tuning managed database instances
  • Scanning code and cloud for vulnerabilities
  • Reducing false-positive triage
  • Auto-fixing findings via pull requests
  • Meeting compliance (ISO 27001, PCI DSS, SOC2)
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