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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

Aura logo
Aura
✓ verifiedPaid

All-in-one digital-safety subscription protecting families from identity theft, fraud and online threats, with parental controls.

2.5M visits/mo762 saves
Flagright AI logo
Flagright AI
✓ verifiedPaid

AML and fraud compliance platform pairing transaction monitoring, screening, and explainable AI agents for financial institutions.

39K visits/mo321 saves
Deep Infra logo
Deep Infra
✓ verifiedPaid

Low-cost inference cloud with developer APIs to run open ML models and on-demand GPUs, billed pay-per-use.

375K visits/mo
Pricing
Kids: $10/mo billed annually
Individual: $12/mo billed annually (1 adult)
Couple: $22/mo billed annually (2 adults)
Family: $32/mo billed annually (5 adults)

Free trial available

No public pricing

No public pricing

Core features
  • Identity theft protection with insurance
  • 3-bureau credit monitoring and lock
  • Antivirus, VPN and password manager
  • Online data removal from brokers
  • Parental controls and safe-gaming alerts
  • Dark-web and financial-fraud alerts
  • Real-time transaction monitoring and rule engine
  • Explainable AI forensics agents
  • Dynamic risk scoring
  • Watchlist/sanctions/PEP screening
  • AI-native case management
  • Automated SAR filing to FinCEN and 70+ GoAML countries
  • Hosted inference for many open models
  • Simple REST/OpenAI-compatible API
  • Pay-per-token or per-time billing
  • On-demand GPU rental
  • Broad catalog (Llama, DeepSeek, Qwen, Flux, etc.)
  • DeepStart and DeepCluster tooling
Use cases
  • Protecting against identity theft
  • Monitoring family credit and finances
  • Keeping kids safe online
  • Removing personal data from broker sites
  • AML compliance and monitoring
  • Reducing false-positive alerts
  • Streamlining fincrime investigations and SAR filing
  • Serving open-source models via API
  • Building AI apps cost-efficiently
  • Renting GPUs for inference or training
  • Scaling inference up and down on demand
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