| What it does | AI agent orchestration platform that models workflow with triggers, actors, stages, gates, permissions, and outcomes
| Production AI at enterprise scale
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| Stage | Not given
| Established
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| Founded | Not given
| 2016
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| Based in | US
| US
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| Pricing model | Not given
| Contact for pricing
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| Pricing | Not given
| Flexible subscription, term, and perpetual licensing models. Organizations switching from conventional architectures see 60-80% reduction in total infrastructure cost. CPU-based pricing with no incremental ETL costs.
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| Key features | - Role-based organization with humans or AI agents in any position
- Workflow definitions with triggers, stages, gates, and outcomes
- Agent-agnostic design supporting Claude, Codex, Gemini, and local models
- Scoped credentials with least privilege access per stage
- Deterministic gates for tests, reviews, and approvals
- Audit trail with hash-chained tamper-evident ledger
- Local-first deployment with optional cloud hosting
- Isolated git worktrees for independent work and verification
- Budget tracking and spend monitoring per organization
- Separation of duties enforced in code
| - AI on Enterprise Data - bring AI directly to governed enterprise data at petabyte scale
- Security - built-in controls for access, governance, and compliance
- Deployment Options - cloud, on-premises, or hybrid deployment flexibility
- Data Ingest - continuously ingest and prepare high-volume data for AI-ready analytics
- Query Optimization - run complex analytics on petabytes of data with predictable performance
- Semi-Structured Data - give AI richer context with structured and semi-structured data in one platform
- Megalane Parallelism - sub-second queries at petabyte scale
- Zero Copy Reliability - no data duplication or redundant storage overhead
- Compute Adjacent Data Store - computation happens where data lives
- Smart Data Pipelines - continuously governed data pipelines replace manual ETL
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| What makes it different | - Orchestration layer that treats work as executable processes rather than remembered habits or wikis
- Roles swappable between humans and AI agents without rewriting workflows
- Credentials and secrets held by infrastructure, never exposed to AI models
- Autonomous AI decision-making within defined stages, deterministic controls at stage boundaries
| - Petabyte-scale performance without moving or duplicating enterprise data
- 60-80% reduction in infrastructure costs compared to conventional architectures
- Production-grade AI delivery with expert implementation and solutions delivery teams
- Flexible licensing models aligned to how enterprise AI programs actually scale
- Unified platform for ingest, governance, query execution and optimization
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| Free plan | Not given
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| Open source | Not given
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| Platforms | Not given
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| Public API | Not given
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 24 ▲ +1 (up) since last check | 54 ● no change since last check |
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| Trust Flow (Majestic) | 7 | 16 |
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| Citation Flow (Majestic) | 31 | 38 |
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| Referring domains (Majestic) | 18 | 361 |
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