The native language of AI; in human terms, a protocol.
Stage
Not given
Startup
Founded
Not given
2026
Based in
US
CA
Pricing model
Paid
Open source
Pricing
Usage-based pay-as-you-go pricing with hourly compute charges; committed contracts available for volume discounts. Hosted option with Anyscale-managed infrastructure or Bring Your Own Cloud deployment available.
Not given
Key features
Multimodal data curation at scale
Distributed model training with elastic scaling
Batch embedding generation at scale
Multi-cloud deployment and orchestration
Cluster-backed development environments
Workload-specific observability and debugging
Production-grade managed Ray clusters
Access control and governance
GPU budget controls and cost attribution
Post-training with SkyRL and veRL support
AI-native communication protocol with 88 verbs and two syntaxes
AI See: give any AI model vision by pasting i.ilang.ai URLs
Zero installation required, pure text format
Works across ChatGPT, Claude, Gemini, DeepSeek, Qwen and other models
Loader available via pip and npm for automatic protocol injection
Prompt compression: 67% reduction in tokens for typical instructions
What makes it different
Built by creators of Ray, the world's most widely adopted AI compute engine
Multi-cloud deployment without code changes
Feels local but runs distributed
Unified GPU pooling across clouds and regions
First protocol to formally map Greek mathematical symbols as primitive verbs for AI-to-AI communication
Computable vector space for AI judgment using 11 dimensions and fuzzy mathematics instead of binary classification
Open source and MIT licensed with no royalties or approval required
Operates at the instruction and behavioral layer, complementary to MCP and A2A protocols
Tested and benchmarked with public conformance results and DOI-registered research
iLang Inc.