---
license: apache-2.0
language:
  - en
  - it
  - multilingual
library_name: transformers
pipeline_tag: question-answering
tags:
  - matrix-bios
  - rag
  - retrieval
  - grounded-generation
  - citations
  - enterprise
---

<p align="center"><b>MATRIX&nbsp;BIOS</b> · <b>Memory</b></p>
<p align="center"><i>Grounded, citation-faithful recall over your private knowledge.</i></p>

# Matrix-BIOS-Memory-0.1

**Developer:** Agent-Matrix · **Version:** 0.1 · **Task:** grounded retrieval &
recall · **License:** Apache-2.0

Memory is the **grounded-recall component** of the **Matrix BIOS** family. It
answers questions **with citations** drawn from a private corpus — so responses are
traceable to their sources instead of hallucinated. It is the enterprise answer to
the central weakness of general LLMs: **a general model cannot cite a private
corpus it has never seen.**

## Model overview

- **Architecture:** retrieval-augmented generation — a semantic vector index over
  your corpus plus a compact grounded generator.
- **Key property:** every answer returns the **source identifiers** it relied on
  (citation faithfulness).
- **Optimised for:** on-premise / sovereign deployment over confidential corpora;
  no data egress.

## Intended use

**Primary use cases**
- Grounded question answering over an organisation's own documents, with provenance.
- The memory plane for governed agents that must explain *why* they answered.
- Trustworthy retrieval where auditability and data residency matter.

**Out of scope**
- Open-domain factual QA outside the indexed corpus.
- High-stakes decisions without human verification of the cited sources.

## How to use

This package ships a semantic index, configuration, and a serving interface that
exposes retrieval and an OpenAI-compatible grounded-answer endpoint, ready to plug
into a gateway or agent runtime. Point it at your own corpus to ground answers in
your private knowledge.

## Limitations & responsible use

A **v0.1 early-access** release. Answer quality depends on corpus coverage and
retrieval quality; always verify cited sources for consequential use. The grounded
generator is a compact model and may paraphrase imperfectly.

## Governance

Memory provides **provenance-cited** recall and operates under Matrix OS
governance: memory writes carry source and trust metadata, and consuming actions
are gated and auditable.

## Citing this work

Matrix BIOS models implement the governed-memory architecture described in our
paper. If you use them in research or production, please cite:

> Magaña Vsevolodovna, R. I. (2026). *Governed Memory: A Bio-Inspired,
> Governance-First Memory Architecture for Continual AI Systems* (1.0). Zenodo.
> https://doi.org/10.5281/zenodo.20615572

```bibtex
@misc{magana2026governedmemory,
  title     = {Governed Memory: A Bio-Inspired, Governance-First Memory
               Architecture for Continual AI Systems},
  author    = {Maga{\~n}a Vsevolodovna, Ruslan Idelfonso},
  year      = {2026},
  publisher = {Zenodo},
  version   = {1.0},
  doi       = {10.5281/zenodo.20615572},
  url       = {https://doi.org/10.5281/zenodo.20615572}
}
```

The concept DOI [10.5281/zenodo.20615571](https://doi.org/10.5281/zenodo.20615571)
always resolves to the latest version.

## License & contact

Released under the **Apache-2.0** license. © Agent-Matrix.
Contact: **contact@ruslanmv.com** · https://ruslanmv.com