| What it does | Production infrastructure for AI applications with observability, governance, and multi-model support
| 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 | Not given
| US
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| Pricing model | Not given
| Contact for pricing
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| Pricing | Personal $15/month (25,000 credits); Starter $25/month (50,000 credits); Team $75/month (100,000 credits); Pro $375/month (500,000 credits). Additional credits available at $0.10 per 1,000 credits.
| 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 | - Step-level observability with traces showing status, latency, credits, and governance for every step
- Natural-language governance policies with flag and block thresholds
- Model portability: swap 200+ models at any time without code changes
- Automatic content ingestion and vector database indexing for RAG
- Persistent memory banks for conversation context
- Cost tracking per model, agent, and step with credit-based pricing
- Structured output validation ensuring quality responses
- HTTP endpoints for every agent with SDKs for Python, JavaScript, Go, and C#
- ML-based prompt scanner blocking injection attacks in real time
- Evaluation framework with evals that run locally, in CI, and in production
| - 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 | - All production LLM features unified in one runtime with no orchestration stack to assemble
- Local development environment matches production exactly for debugging and verification
- Swap between 200+ models without changing code or workflow logic
- Governance and compliance built-in with real-time prompt injection blocking and policy evaluation
- Transparent credit-based pricing where all operations consume predictable, tracked credits
| - 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) | 8 ▼ −1 (down) since last check | 54 ● no change since last check |
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| Trust Flow (Majestic) | 6 | 16 |
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| Citation Flow (Majestic) | 20 | 38 |
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| Referring domains (Majestic) | 22 | 361 |
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Seclai
Ocient