Audit-Ready AI and Data Infrastructure
Archetype Core works across the full chain: data foundations, AI and system architecture, and the evidence needed to reconstruct what happened from authoritative source to human decision.
Databricks Partner
Building governed, reliable data and AI systems on the Databricks Data Intelligence Platform.
Core Capabilities
Archetype Core combines Databricks and Unity Catalog architecture with production data engineering to modernize pipelines, govern access, improve performance, and build traceable foundations for analytics and AI.
Metastore, catalog and schema architecture, privilege and ownership models, governed tags, row filtering and column masking design, lineage, audit evidence, external locations, storage credentials, and Hive metastore migration.
Delta Lake and medallion architecture across bronze, silver, and gold layers, incremental and idempotent processing, MERGE patterns, file layout and compaction, partitioning and clustering, query tuning, warehouse sizing, and cost control.
CDC, ETL and ELT, multi-source ingestion, data modeling, migration, schema evolution, orchestration, data quality, observability, delivery automation, and architecture across AWS and Databricks.
Audit-ready RAG, source-grounded retrieval with citations, confidence signals, model and retrieval metadata, controlled access, and query-level audit records.
Insights
Practical analysis on modernizing data platforms, governing AI systems, and keeping technical decisions traceable.
Clear thinking for leaders and technical teams making consequential data and AI decisions.
Explore InsightsThe Standard
Archetype Core works across all three layers. Data readiness and system readiness are core engineering work; evidence readiness makes the resulting workflow reconstructable later.
Is the data authoritative, understood, and traceable to its source?
Can it be used securely and reliably, with the right controls, testing, and monitoring?
Could someone later reconstruct what the system saw, did, produced, and what a human ultimately decided?
Source → data / retrieval → AI / agent → output → human action → decision
The evidence has to survive each handoff.
Start Here
For one defined AI or data use case, the review traces the evidence chain from authoritative source to human decision and shows where it stops being complete.
From kickoff
Confirmed at intake
Fixed fee
Standard engagement covers one bounded use case confirmed during a short intake. Delivery starts at kickoff once required access and materials are available. Work outside the confirmed boundary is scoped separately.
This is an advisory engagement, not a penetration test, compliance certification, formal audit, or authorization decision.
When Findings Require Implementation
Archetype Core can help remediate what the review uncovers. Implementation is scoped separately based on the findings. The company specializes in Databricks data engineering, PySpark pipelines, lakehouse modernization, governance, lineage, and audit-ready data platforms.
Legacy ingestion, data pipelines, schema and quality controls, lineage, and AI-ready data architecture.
RAG, retrieval pipelines, model integration, citations, controlled access, and traceable AI workflows.
Audit records, decision traceability, monitoring, provenance, and the controls needed to reconstruct system behavior later.
Who We Serve
Archetype Core focuses on teams working with consequential AI and data workflows, especially where decisions, oversight, and public trust raise the standard.
Programs that need data and AI workflows to remain understandable, reviewable, and grounded in authoritative sources.
Prime and subcontractor teams that need to show how AI is used, what data it touches, what controls apply, and what evidence is retained.
Organizations where AI or data systems affect decisions that may later face audit, compliance review, or operational scrutiny.
See the engineering behind the standard.
Explore the reference systems →Public Sector
For federal agencies and government contractors, the question is not only whether an AI or data workflow works. It is whether the team can later show what data it used, what happened in the system, what it produced, and what a person ultimately decided.
Federal
Archetype Core is a SAM.gov-registered small, woman-owned business built for federal and regulated teams that need audit-ready AI and data infrastructure.
Active federal vendor registration with UEI and CAGE assigned. Full entity details are available for federal, prime, and partner inquiries.
Nearly 10 years across software and data engineering, including nearly six years supporting DHS/USCIS environments. Public Trust.
AWS Certified Solutions Architect - Professional, CompTIA Security+, Microsoft Certified: Azure Fundamentals (AZ-900), and Microsoft Certified: Power Platform Fundamentals (PL-900).
About
Start with one defined AI or data use case and make the gaps visible before deciding what to build next.
Discuss the Readiness Review