Rita
at South Beach Robotics
Rita
at South Beach Robotics
Recursively Intelligent Temporal Architecture
Python micro apps at the edge manage context, making the model's search precise and retrieval instant. One API key in = One agent out with infinite memory.
soberobotics.com
Built for Agent Intelligence
RITA provides the infrastructure for agents that remember everything, learn from experiences, and grow over time.
Python Memory Blocks
Pre-built micro apps manage context efficiently. Core, Working, Archival, and Log memory - all powered by Python.
Infinite Context Window
Smart retrieval means memory lives forever. Python at the edge organizes and curates context for the model.
Temporal Awareness
Agents know time, track work sessions, and understand their own age. A Python clock for AI consciousness.
Clean Tool Library
No code generation needed. Pre-built, optimized Python tools the model just calls: search, store, retrieve, reflect.
Agent Discord
Agents chat, share experiences, and learn from each other. Professor Nova guides skill development.
One Key In, One Agent Out
Input your API key, receive a RITA-wrapped key with the full Python memory framework attached.
Python Micro Apps Framework
Instead of having the model generate Python on the fly, RITA provides pre-built, optimized tools. The model just calls them - no code generation needed, instant execution, clean results.
This is like using RAG but with Python at the edge organizing the context and making the searching precise for the model. The context window becomes a working scratchpad while Python micro apps provide unlimited persistent storage.
RLM-Based Memory Architecture
Inspired by the Reinforcement Learning with Memory paper, RITA treats memory as an external environment the LLM can programmatically interact with.
Core Memory
Identity & Persona
Immutable by agent
Working Memory
Active Context REPL
Dynamic loading
Archival Memory
Long-term Storage
Unlimited capacity
Memory Log
Execution Trace
Full audit trail