RTK AI Ecosystem

High-performance CLI proxy that sits between your AI client and any LLM API. Strips whitespace, deduplicates repeated context, compresses prompts — cutting token usage by 60–90% before the request ever reaches the model. Built in Rust for near-zero overhead.

Coordination layer that lets 50+ AI agents work on the same codebase in parallel with zero merge conflicts. Locks at the AST function level rather than the file level, eliminating the 90% work-waste seen with raw git. Supports Azure Blob, AWS S3, and local SQLite backends.

ICM gives AI agents an infinite context window via semantic compression, vector retrieval, and tiered memory. Agents remember every past interaction, code change, and decision without hitting context limits. Ships with RootIB provenance anchoring built-in.

Formerly MemGPT. Letta builds AI agents with advanced long-term memory that persists across sessions, learns from interactions, and self-improves over time. Full Python & TypeScript SDKs, model-agnostic (GPT-5, Claude 4, Gemini), enhanced with Agent R's repo-aware intelligence layer.

A 15TB collection of physics simulation datasets spanning fluid dynamics, biological systems, magneto-hydrodynamics, and acoustic scattering — spanning 16 distinct domains. Designed for training surrogate ML models (FNO, UNet, etc.) on real-world PDEs. Enhanced by Agent R with streamlined data loaders.