Cloud backend for AI-operated products with hosting, payments, and MCP integration
Production AI at enterprise scale
Stage
Not given
Established
Founded
Not given
2016
Based in
Not given
US
Pricing model
Not given
Contact for pricing
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.
Key features
MCP integration with ChatGPT, Claude, Grok, and Cursor
Authentication and data management
Payment processing
REST API
Knowledge and RAG systems
Project hosting
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
What makes it different
Unified backend for multiple AI models and platforms
Works with any MCP-capable AI
All-in-one operational tooling for AI products
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
AgentStack
Ocient