A framework for AI systems that maintain meaningful continuity across interactions, contexts, and time.
This project treats memory as lived contextual experience so agents can retain skills, world models, and performance history across sessions. The goal is to enable safe, reliable long-term collaboration between humans and AI in shared organizational and personal environments.
- Layered memory for episodic, semantic, and procedural experience
- Skill retention across sessions and multi-session task resumption
- Performance awareness, drift/degradation monitoring, and adaptive compensation
- Safety-first incident memory, explainable recall, and governance-aware retention
Early research and framework design. APIs and storage formats are expected to change.
| Field | Value |
|---|---|
| Hardware | CPU-first; no GPU or CUDA required |
| Acceleration | Optional (hardware-agnostic) |
| Project Name | edyant |
| Description | Framework for AI systems that maintain continuity across interactions, contexts, and time |
| Python Requirement | Python >= 3.11 |
| License | Apache License 2.0 |
| Author | Edyant Labs |
| Contact | arsalan@edyant.com |
python -m pip install edyantTest releases (TestPyPI):
python -m pip install \
--index-url https://pypi.org/simple \
--extra-index-url https://test.pypi.org/simple/ \
edyantimport edyantfrom edyant import benchmark
from edyant import core
from edyant import ethics
from edyant import persistence
from edyant import persona
from edyant import umweltSee about.md for the full framework narrative, research threads, and governance considerations. The license is in LICENSE.