Archetype Core — Audit-Ready AI Systems

The Problem

Most AI systems cannot answer the questions that matter.

Organizations are deploying AI faster than they can govern it. When something goes wrong, the same questions appear, and most systems cannot answer them.

Provenance

Which documents, records, or prompts produced this answer?

Reproducibility

Which model version ran, and can the exact decision be reconstructed later?

Accountability

Can this system hold up under compliance review, legal scrutiny, or internal audit?

Start Here

The fastest way to work together.

AI-Ready Data Infrastructure Assessment

A focused review of your current data and AI architecture to identify governance gaps, traceability risks, and the fastest path to an audit-ready system.

Best for

Teams adopting AI in regulated or high-trust environments.

Deliverables

Architecture review, risk map, decision-traceability recommendations, and next-step roadmap.

Outcome

Clarity on what to fix now before an AI workflow becomes expensive to unwind later.

Request an Assessment Request Capability Statement →

What We Do

Architecture first. Hype never.

We specialize in regulated environments where compliance, audit trails, and traceability are baseline requirements.

Data Platform Architecture

Cloud-native platforms, pipeline design, warehouse strategy, and the data foundations everything else depends on.

AI Infrastructure & RAG

Retrieval pipelines, LLM integration, source citation, and production AI that can explain itself.

Governance & Reliability

Audit trail design, data lineage, and controls that let you tell a regulator exactly what happened and why.

Who We Serve

Built for industries where trust is the product.

Most AI systems fail not because they are inaccurate, but because they cannot be trusted.

If your organization handles sensitive data, answers to regulators, or depends on AI systems that must be trusted, the architecture behind those systems matters.

Federal Contractors

Building AI systems that can pass compliance reviews, not just demos.

Healthcare & Compliance

Adopting AI without putting patient data, governance, or regulatory posture at risk.

Financial Services

AI systems that can withstand audits, investigations, and control reviews, not only perform in testing.

Law Firms & Legal Tech

Answers that can be cited, defended, and trusted in real document-heavy workflows.

See how this works in a real system.

Explore the audit-ready case study →

Public Sector

See how this applies to government agencies.

Public agencies handle policy documents, program guidance, and public information that must be answered consistently, cited accurately, and reviewed under scrutiny. This is the use case the architecture was built for.

Explore Public Sector

About

Built by someone who has done this work in production.

Mariana Lungu is a data architect specializing in traceable AI systems for regulated environments. Her background includes more than eight years of experience building data infrastructure, with the majority of that work in federal environments where governance, compliance, and auditability are baseline requirements.

Archetype Core exists for teams that need more than a proof of concept. Systems are designed to be traceable. Pipelines are built to be auditable. AI integration is done with guardrails, citation provenance, and decision lineage from the start.

The Audit-Ready RAG System is a live example of this approach. It demonstrates how document retrieval, model behavior, and answer provenance can be structured in a way that is practical, production-minded, and ready for scrutiny.

We build AI systems that can survive an audit.