Data contract first
Schema, ownership, and allowed uses are written down before ingestion, so the system never quietly depends on a field nobody agreed to.
Collect, structure, govern.
What a CEO/CTO needs to know
The fastest model on earth cannot recover from bad data discipline. Ask to see the data contract before you ask to see the demo.
Source to contract to retrieval, with PII tagged at the schema boundary so it never reaches the prompt.
Data is the substrate of every AI feature. Schema, lineage, retention, and consent boundaries get defined before we train, fine-tune, or prompt. Discipline here is what keeps PII out of a completion and lawyers off the phone.
Schema, ownership, and allowed uses are written down before ingestion, so the system never quietly depends on a field nobody agreed to.
Every value is traceable from source through retrieval, so when an answer is wrong you can find which input made it wrong.
Sensitive fields are tagged at the schema level and blocked at prompt assembly. Retention matches the firm's compliance window, reviewed, not assumed.
Four rungs from absent to production-grade. Level 3 is the target, and the only one that survives a real production incident.
Data is ingested as found. No schema, no lineage, no PII boundary.
Schemas exist per source but drift, and PII handling is manual and inconsistent.
A data contract and retention policy exist, but lineage and PII gating are partial.
Contract-first data, lineage from source to retrieval, PII tagged and gated, retention reviewed against compliance.
You do not need to read the code. Ask these questions and demand these artifacts. Vague answers are the finding.
Ingesting whatever is available and hoping the model cleans it up. RAG over a hairball. PII surfacing in completions. Lawyers calling.
We run the K-Framework against your AI build and hand you the gap list, ranked by what it will cost you in production.