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Cloud-agnostic AI/ML workflow orchestrator that runs pipelines inside a customer's own infrastructure for compute-heavy teams.
Automated AWS usage optimization platform giving engineers 150+ recommendations across 50+ services, averaging ~10% savings.
Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
Local deep packet inspection and network intelligence giving businesses full visibility into application, VPN and Tor traffic.
Unified API gateway to 500+ AI models (GPT, Claude, Sora, image/video) with OpenAI-compatible endpoints and discounted usage.
Free trial available
No public pricing
Free trial available
No public pricing
No public pricing
- ✦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
- ✦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
- ✦Publish structured documentation sites
- ✦Git sync for docs-as-code workflows
- ✦AI setup agent to build and import docs
- ✦GitBook MCP server for AI access
- ✦Enterprise controls
- ✦Free tier to start
- ✦Local deep packet inspection agent
- ✦Application identification data feeds
- ✦VPN and Tor IP datasets
- ✦Network informatics and analytics
- ✦Developer documentation
- ✦Single OpenAI-compatible API for 500+ models
- ✦Chat, image, video and audio models
- ✦Discounted per-request pricing
- ✦One dashboard for keys, quotas and usage
- ✦Multi-region routing and failover (99.9% uptime)
- ✦Multiple payment methods incl. crypto
- →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
- →Cutting AWS spend automatically
- →Rightsizing over-provisioned resources
- →Scheduling idle resources off-hours
- →Giving DevOps in-console cost recommendations
- →Publish product and API documentation
- →Maintain docs-as-code with Git sync
- →Make docs consumable by AI assistants
- →Import existing docs into a hosted site
- →Classify application traffic on a network
- →Detect VPN and Tor usage
- →Feed DPI data into security and analytics tools
- →Accessing many AI models via one API
- →Cutting AI model API costs
- →Building multimodal AI apps
- →Consolidating AI billing and keys
