Proto-AGI research, open source model recipes and HPC infrastructure
Stage
Established
Not given
Founded
2016
Not given
Based in
US
US
Pricing model
Contact for pricing
Open source
Pricing
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.
Not given
Key features
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
Open source model recipes for GLM-5.3
TensorFold deployment tool
Memory, identity and model orchestration research
1M context window support
Task and workflow benchmarks
Proto AGI Engine with coordinated model roles
Multiple concurrent request handling
What makes it different
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
Ocient
Aevonix Research