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Union Cloud
✓ verifiedPaid
Cloud-agnostic AI/ML workflow orchestrator that runs pipelines inside a customer's own infrastructure for compute-heavy teams.
25K visits/mo
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The New GitBook
✓ verifiedFreemium
Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
653K visits/mo2.9K saves
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Released
✓ verifiedFreemium
Jira-native tool that turns existing issues into customer roadmaps, release notes, and feedback portals without duplicate data entry.
11K visits/mo941 saves
Pricing
Team: $950/month + usage (1,000 concurrent actions, 30-day retention, 1 cluster)
No public pricing
Free trial available
Free: $0/mo (up to 10 users, 2,000 AI tokens/user)
Standard: $1.10/user/month (unlimited users, 10,000 AI tokens/user)
Advanced: $1.70/user/month (unlimited users, 20,000 AI tokens/user)
Free trial available
Core features
- ✦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
- ✦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
- ✦Roadmaps synced live from Jira issues
- ✦AI-generated release notes
- ✦Customer feedback and idea portals
- ✦Audience-specific roadmap views
- ✦Password-protected or invite-only sharing
- ✦Publishing to Confluence and Slack
Use cases
- →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
- →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
- →Sharing a public product roadmap with customers
- →Publishing release notes automatically from Jira tickets
- →Collecting and prioritizing customer feature requests
- →Giving executives a curated view of product progress
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