MAGI for legal document processing - metadata compliance questions

[shireenbosher45]

I work in e-discovery and we process thousands of documents for litigation. MAGI's structured metadata looks promising for our use case, but I have some compliance questions:

1. The doc-id field uses UUID - is there support for existing document numbering systems (like Bates numbers)?
2. Can the front matter be extended with custom fields for chain-of-custody tracking?
3. For the expired-date field - in legal contexts, document retention policies are strict. Is this field intended for content validity or could it drive automated retention workflows?

The relationships via footnotes could be huge for mapping privilege logs and document families.

[adoniyahbobay26]

These are really practical questions. Looking at the spec:

1. The front matter is YAML, so you can absolutely add custom fields like bates-number or matter-id. MAGI parsers should ignore fields they don't recognize.
2. For chain-of-custody, you could extend with fields like custodian, collection-date, processing-hash. Since it's YAML, the schema is flexible.
3. The expired-date is currently described as content validity, but there's no reason a processing pipeline couldn't use it for retention automation.

The real power for e-discovery would be combining footnote relationships with the entities field to build document-family graphs automatically.

[jakhyiakutler25]

From an analytics perspective, the tags and entities fields combined with relationship footnotes could power some serious document clustering. You could feed a corpus of .mda files into a graph database and let the explicit relationships bootstrap your document review.

For privilege detection, an ai-script block could be configured to flag potentially privileged content with specific system-prompt instructions tuned for legal review.

[shireenbosher45]

Both excellent points. The extensible YAML front matter is key for us. I'm going to prototype a pipeline that:

1. Converts our document corpus to .mda using url2mda as a starting point
2. Adds legal-specific metadata via a custom enrichment step
3. Uses ai-script blocks for privilege screening
4. Builds relationship graphs from footnotes

Will share results if it works out. This could be a real differentiator over our current Relativity workflow.