Profile every critical table on a cadence, score AI-readiness with deterministic metrics plus a plain-language rationale, and open one remediation task per real gap — the Sentinel surfaces the problem, never silently rewrites your data. Runs on your infrastructure, against your systems of record, with a full audit trail.
Every AI and analytics initiative quietly fails on the same thing: the core tables underneath it are full of nulls, orphaned foreign keys, duplicates, and format drift that nobody is watching. Copilots and RPA overlays hit a ceiling because the structural issues stay in the core. The gap is invisible until a model hallucinates, a board report is wrong, or a CFO asks why the AI program isn't returning — and today it's certified 'AI-ready' with a spreadsheet and a prayer.
The moment you try to fix it with a tool that 'auto-cleans,' you hand a model the authority to silently mutate your system of record — so nobody can trust what changed, or prove it. Data edits are identity-adjacent. That is exactly the authority you cannot give away.
Days, not a platform rollout. The profiling is pure Code and needs only read access to your tables over a standard REST/OData API — no agents in the core, no schema migration. Point it at 3–5 critical tables with the kill-switch on and it runs shadow-first, so you see the first scored register and high-severity findings before any task reaches a person.
The same pipeline profiles every core table you own — three tables or three hundred.
Turn 'is our data AI-ready?' from a quarterly fire drill into a daily, evidence-backed score per table — null, orphan-FK, duplicate, and format-drift rates computed in auditable Code, not guessed by a model.
Null, orphaned-foreign-key, duplicate, and format-drift gaps surface on the cadence — before they reach a model, a report, or a CFO's question about the AI program.
Exactly one human-owned task per newly-opened, high-severity gap — deduped against the database so re-runs never spawn alert storms or duplicate tickets.
A living register and dashboard that re-renders every run, so late fixes and resolved findings re-aggregate — proof the gap is measurably shrinking over time, not a stale snapshot.
Every finding records the estimated AI-scale value the fix would free on a shared value bus — so data work earns its budget in front of the CFO instead of asking for it on faith.
The Sentinel reads and recommends; a human makes the actual edit. There is no write path back into your core system at all — so you can trust exactly what changed and why.
The model proposes the rationale; a human makes the fix; nothing touching your source data ever auto-fires. It is the same secure spine every flow8 Solution runs — here worn as a data-quality sentinel.
proposed finding on a shared, tamper-evident register — not an edit to your data.proposed finding row keyed by table, column, and rule — never an edit to the source.
draft, not act
Data Quality Sentinel runs on a cadence — daily by default — and pulls a bounded, scoped sample and row counts from each configured core table over your own REST or OData API. It runs the injection pre-scan on every free-text value before any model sees it, then computes the objective data-quality metrics — null, orphan-foreign-key, duplicate, and format-violation rates — in deterministic Code. A schema-locked LLM is then asked for one job only: read the deterministic profile and write a plain-language AI-readiness rationale and remediation recommendation.
Because the numbers and the severity verdict are computed in auditable Code and never sourced from the model, because data edits are capped at prepare-only by construction, and because the finding row is written before any side-effect on a hash-chained, signed register, you get an AI-readiness program without ever handing a model the authority to touch your data. Auto-clean tools give a model write access first and bolt on trust later — flow8 makes the guardrail the architecture, and never writes back to the source at all.
proposed finding and a recommendation, and a human makes the actual edit. There is no write path back into the core system at all.Not rebuilt from scratch — composed from the same governed building blocks every flow8 Solution shares, so it ships in days.
Any business whose AI and analytics rest on core master data that must be certified trustworthy before anyone builds on it.
Adopt this one and it plugs into the spine the others already speak.
Watch your critical tables turn into a daily, evidence-backed AI-readiness register your team can trust — deterministic, auditable, and incapable of silently changing your data. When you're ready, add more tables and rules, wire in value-tracking and reconciliation, or turn on the signed compliance ledger on the exact same pipeline.
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