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AI DevSecOps platform running 32 parallel scanners with an AI engine that cuts false positives and auto-generates fix PRs.
Cloud-agnostic AI/ML workflow orchestrator that runs pipelines inside a customer's own infrastructure for compute-heavy teams.
Continuously analyzes MySQL, MariaDB, and PostgreSQL workloads to recommend and safely apply configuration and query fixes.
FinOps tool that maps cloud and AI spend to the code driving it and auto-generates cost-cutting pull requests.
Local deep packet inspection and network intelligence giving businesses full visibility into application, VPN and Tor traffic.
Free trial available
Free trial available
No public pricing
Free trial available
No public pricing
- ✦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
- ✦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
- ✦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
- ✦Maps cloud costs to the code that drives them
- ✦Cost-impact review on every pull request
- ✦Frugalbot agents that generate cost-reducing PRs
- ✦Coverage of storage, logs, AI APIs, serverless and databases
- ✦GitHub and GitLab workflow integrations
- ✦Local deep packet inspection agent
- ✦Application identification data feeds
- ✦VPN and Tor IP datasets
- ✦Network informatics and analytics
- ✦Developer documentation
- →Scanning code and cloud for vulnerabilities
- →Reducing false-positive triage
- →Auto-fixing findings via pull requests
- →Meeting compliance (ISO 27001, PCI DSS, SOC2)
- →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
- →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
- →Cut usage-based cloud and AI bills
- →Add cost reviews to the development workflow
- →Guide developers and AI agents to write cheaper code
- →Find savings that infrastructure right-sizing misses
- →Classify application traffic on a network
- →Detect VPN and Tor usage
- →Feed DPI data into security and analytics tools