ML

Mariana Lungu · Northern Virginia · --:-- ET

I build systems that can
explain themselves.

I help regulated teams build data and AI systems that can be traced, defended, and trusted after the output leaves the screen.

See the problemWork with me
Mariana Lungu

The problem I solve

Most systems look finished before they are defensible.

The output is polished. The workflow runs. The presentation lands. Then someone asks where it came from, what changed, who touched it, and whether it can be trusted later.

That is the room I am built for: when AI, data, governance, and judgment have to hold together.

01 · AI output

The answer looks clean.

But the team cannot prove which source, prompt, model state, retrieval path, or decision rule produced it.

02 · Data systems

The dashboard moves.

But the lineage is thin, the handoffs are informal, and the record breaks the moment someone asks what changed.

03 · Regulated work

The risk shows up later.

After launch, after adoption, after an audit, after a client asks for proof. That is when architecture matters.

When to bring me in

  • AI pilots need governance before they become production systems.
  • Data platforms need lineage before leaders rely on the metrics.
  • Teams need a standard before speed becomes institutional risk.

The standard

I do not trust output I cannot trace.

Before I trust a system, I look for the record underneath it. Not a screenshot. Not a promise. A path someone else can inspect.

Question 01
Where did it come from?
Question 02
Can it be reproduced?
Question 03
What changed after it shipped?
Question 04
What happens when the system is unsure?

Operating standard

A trusted system keeps the record with the answer.

01 · Provenance

The record comes before the answer.

Source, retrieval path, confidence, and decision context stay attached so the work can be defended later.

Live trace · 12:51 PM ET

Policy passage

The answer starts with cited source material, not a generated guess.

Confidence
0.91
Hash
SHA
Action
Review

The receipt

I built a retrieval system on federal policy documents to prove the standard instead of describing it. Every answer carries its evidence, decision context, and audit trail.

Record 01

automated tests behind the retrieval pipeline

44

This is the kind of receipt a buyer can inspect: not just what shipped, but how it was tested, traced, and made defensible after the fact.

Record 02

policy passages indexed with lineage

9,116

This is the kind of receipt a buyer can inspect: not just what shipped, but how it was tested, traced, and made defensible after the fact.

Record 03

audit fields recorded for every answer

16

This is the kind of receipt a buyer can inspect: not just what shipped, but how it was tested, traced, and made defensible after the fact.

Record 04

content hashing on every indexed record

SHA-256

This is the kind of receipt a buyer can inspect: not just what shipped, but how it was tested, traced, and made defensible after the fact.

The technical practice

Archetype Core

Audit-ready AI and data infrastructure for regulated teams: traceable pipelines, cited answers, reproducible decisions, and governance that can be inspected after launch.

The art house

The Ferne

Original mixed media work made slowly, with restraint, texture, and private meaning. Structure is how I work. Feeling is why.

The public ledger

Beyond the Prompt

Notes on AI, provenance, governance, systems, and the work underneath reliable output. This is where I make the standard visible in public.

Still life of folded linen, ceramic vessel, and a sheet of paper in soft daylight

The origin

The decade that made the standard.

Federal systems, immigration cases, benefits processing, congressional inquiries: data that touched real people and had to be right. That is where my sense of provenance came from.

I learned to build where almost right was not good enough: where handoffs mattered, records had to survive scrutiny, and the quiet work underneath the visible system decided whether people could trust it.

This site is not my résumé. It is the public signal of that standard, and why I should be the person in the room when the system has to stand up later.

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