Shodh-Memory
Persistent cognitive memory for AI agents and robots — with no LLM in the loop. Remembers what matters, forgets what doesn't, gets smarter with use.
AI agents forget everything between sessions. Robots lose context between missions. They repeat mistakes, miss patterns, and treat every interaction like the first one.
Shodh-Memory fixes this. It's persistent memory that actually learns — memories you use often become easier to find, old irrelevant context fades automatically, and recalling one thing brings back related things. Works for chat agents (MCP/HTTP), robots (Zenoh/ROS2), and edge devices. No API keys. No cloud. No external databases. No LLM in the loop. One binary.
Why Not Just Use mem0 / Cognee / Zep?
| Shodh | mem0 | Cognee | Zep | |
|---|---|---|---|---|
| LLM calls to store a memory | 0 | 2+ per add | 3+ per cognify | 2+ per episode |
| External services needed | None | OpenAI + vector DB | OpenAI + Neo4j + vector DB | OpenAI + Neo4j |
| Time to store a memory | 55ms | ~20 seconds | seconds | seconds |
| Learns from usage | Yes (Hebbian) | No | No | No |
| Forgets irrelevant data | Yes (decay) | No | No | Temporal only |
| Runs fully offline | Yes | No | No | No |
| Robotics / ROS2 native | Yes (Zenoh) | No | No | No |
| Binary size | ~17MB | pip install + API keys | pip install + API keys + Neo4j | Cloud only |
