SOX data governance framework for enterprise LLM deployment — Reference Architecture

Reference architecture · published 2026-10-16 · regulated enterprise · SOX · layout diagram_first · implementation executed in CI before publish

The control that resolves this is a Classification-Routed Multi-Cloud Estate, evaluated before the request reaches a model provider rather than audited afterwards. In regulated enterprise the binding constraint is SOX, and the question it actually asks is can an AI-influenced number in a filing be traced and reproduced. The shape below holds p95 ≤ 600ms over REST over HTTPS, and ships with a standard-library implementation that runs as written.

The blueprint

Classification-Routed Multi-Cloud Estate — the request path, with the decision points that must exist before the first model call:

flowchart TB
    IN[Request payload] --> CLS[Deterministic classifier<br/>regex + Luhn/checksum]
    CLS --> LV{Classification}
    LV -->|PUBLIC / INTERNAL| D1[shared-us]
    LV -->|CONFIDENTIAL| D2[eu-pooled<br/>DPA required]
    LV -->|RESTRICTED| D3[eu-dedicated<br/>zero-retention + subprocessors]
    LV -->|no lawful destination| DN[Deny + reason]
    D1 --> LOG[(Decision log)]
    D2 --> LOG
    D3 --> LOG
    DN --> LOG
    D3 --> LIN[Lineage tag on<br/>embeddings / cache / evals]
    ATT[Destination attestations] -.-> LV
    ATT --> DR[Drift detector]

Implementation components

1. Deterministic classifier — Pattern plus validator (Luhn, checksum) so the gate does not cry wolf.
2. Destination attestations — Region, max class, retention, DPA, subprocessor disclosure — as data.
3. Routing gate — First lawful destination in preference order; cost can never override a control.
4. Decision log — A recorded reason for every allow AND every deny.
5. Lineage tags — Classification travels with derived artifacts: embeddings, caches, evals.
6. Drift detector — Alerts when a destination's attested properties change.

Enterprise implementation parameters

Every value below is a parameter you can hold a vendor or an internal team to. Adjectives are not acceptance criteria.

Where the rollout actually stalls

Workloads span several providers and regions, and the decision of which model may see which data lives in prompt text, a wiki page, or a developer's judgement. That is not a control, so the governance board cannot approve the estate even though every individual component is defensible.

What SOX specifically requires

SOX cares about the integrity of financial reporting. If a model output touches a number that reaches a filing, the control question is whether that output can be reproduced exactly and attributed to a reviewed, approved version.

The artifact that satisfies it is reproducible output records pinned to a model version. The way teams most often fail it: a model upgrade changing a reported figure with no record of which version produced the original.

Implementation artifact — Classification-driven routing gate with recorded reasons

Standard-library Python, no external dependencies, runs as written. Executed by the publish gate: if it raises, this page does not ship. Wire it behind REST over HTTPS; the failure mode it guards against is a retried POST creating a duplicate record. The output you hand the assessor is the reporting-period reproducibility record.

"""Classification-driven routing gate for a multi-cloud LLM estate.

Why this shape: "which model may see this data" is a governance decision, and
if it lives in prompt text or a developer's judgement it is not a control. It
has to be a deterministic function of the data's classification and the
destination's attested properties, evaluated before egress.

The gate below is the smallest thing that an actual data-governance board will
accept: classification in, allowed destinations out, with a recorded reason for
every allow and every deny.
"""
import re
from dataclasses import dataclass
from enum import IntEnum


class Class(IntEnum):
    PUBLIC = 0
    INTERNAL = 1
    CONFIDENTIAL = 2
    RESTRICTED = 3      # PII / PHI / material non-public


DETECTORS = {
    "email": re.compile(r"[\w.+-]+@[\w-]+\.[\w.]{2,}"),
    "iban": re.compile(r"\b[A-Z]{2}\d{2}[A-Z0-9]{10,30}\b"),
    "card": re.compile(r"\b(?:\d[ -]?){13,19}\b"),
    "ssn": re.compile(r"\b\d{3}-\d{2}-\d{4}\b"),
    "mrn": re.compile(r"\bMRN[:\s-]*\d{6,10}\b", re.I),
}


def luhn(number: str) -> bool:
    """Card detectors without Luhn produce false positives on order numbers,
    and a gate that cries wolf gets switched off."""
    digits = [int(c) for c in re.sub(r"\D", "", number)]
    if len(digits) < 13:
        return False
    checksum, parity = 0, len(digits) % 2
    for i, d in enumerate(digits):
        if i % 2 == parity:
            d *= 2
            if d > 9:
                d -= 9
        checksum += d
    return checksum % 10 == 0


def classify(text: str, floor: Class = Class.INTERNAL) -> tuple:
    """-> (classification, evidence). Deterministic and explainable."""
    found = []
    for name, rx in DETECTORS.items():
        for m in rx.finditer(text or ""):
            if name == "card" and not luhn(m.group(0)):
                continue
            found.append(name)
            break
    return (Class.RESTRICTED if found else floor), sorted(set(found))


@dataclass(frozen=True)
class Destination:
    name: str
    region: str
    max_class: Class
    zero_retention: bool
    dpa_signed: bool
    subprocessors_disclosed: bool


class Denied(Exception):
    pass


def route(text: str, destinations: list, required_region: str = None) -> dict:
    """Pick the first destination whose ATTESTED properties cover the data.

    Order matters: destinations are supplied in preference order (cheapest or
    fastest first) and the gate takes the first one that is lawful, so cost
    optimisation can never override a control.
    """
    level, evidence = classify(text)
    reasons = []
    for d in destinations:
        if d.max_class < level:
            reasons.append(f"{d.name}: max_class {d.max_class.name} < {level.name}")
            continue
        if required_region and d.region != required_region:
            reasons.append(f"{d.name}: region {d.region} != {required_region}")
            continue
        if level >= Class.RESTRICTED and not d.zero_retention:
            reasons.append(f"{d.name}: retains prompts, unusable for {level.name}")
            continue
        if level >= Class.CONFIDENTIAL and not d.dpa_signed:
            reasons.append(f"{d.name}: no DPA on file")
            continue
        if level >= Class.RESTRICTED and not d.subprocessors_disclosed:
            reasons.append(f"{d.name}: subprocessors undisclosed")
            continue
        return {"allowed": True, "destination": d.name,
                "classification": level.name, "evidence": evidence,
                "rejected": reasons}
    raise Denied(f"no lawful destination for {level.name} data: {reasons}")


if __name__ == "__main__":
    dests = [
        Destination("shared-us", "us-east-1", Class.INTERNAL, False, True, False),
        Destination("eu-pooled", "eu-west-1", Class.CONFIDENTIAL, False, True, True),
        Destination("eu-dedicated", "eu-west-1", Class.RESTRICTED, True, True, True),
    ]
    print(route("Summarise this quarter's churn drivers.", dests))
    print(route("Patient MRN 4471902 reports side effects.", dests,
                required_region="eu-west-1"))
    try:
        route("Card 4111111111111111 was declined.",
              [d for d in dests if not d.zero_retention])
    except Denied as e:
        print("correctly denied:", str(e)[:96])

The SOX control, as code

Segregation of duties over model releases. This is the artifact an assessor asks for under SOX specifically — it is not the same control as the one above, and a system that implements one does not thereby implement the other. It executes under the same publish gate.

"""Segregation of duties over model releases, with an immutable approval chain.

SOX cares about change management over systems affecting financial reporting.
The control that fails is the one where the person who wrote the change also
approved and deployed it, and where the approval record can be edited after the
fact. Both are structural, so both are enforced here rather than reviewed.
"""
import hashlib
import json


class ApprovalChain:
    """Append-only. Each link commits to the previous digest, so an edited
    record breaks verification rather than quietly rewriting history."""

    def __init__(self):
        self.links: list[dict] = []

    def _head(self) -> str:
        return self.links[-1]["digest"] if self.links else "genesis"

    def append(self, action: str, actor: str, change_id: str) -> dict:
        body = {"action": action, "actor": actor, "change_id": change_id,
                "prev": self._head()}
        digest = hashlib.sha256(
            json.dumps(body, sort_keys=True).encode()).hexdigest()
        link = dict(body, digest=digest)
        self.links.append(link)
        return link

    def verify(self) -> bool:
        prev = "genesis"
        for link in self.links:
            body = {k: link[k] for k in ("action", "actor", "change_id", "prev")}
            if link["prev"] != prev:
                return False
            if hashlib.sha256(
                    json.dumps(body, sort_keys=True).encode()).hexdigest() != link["digest"]:
                return False
            prev = link["digest"]
        return True

    def actors(self, change_id: str, action: str) -> set[str]:
        return {l["actor"] for l in self.links
                if l["change_id"] == change_id and l["action"] == action}


class ReleaseGate:
    def __init__(self, chain: ApprovalChain):
        self.chain = chain

    def author(self, change_id: str, actor: str) -> None:
        self.chain.append("author", actor, change_id)

    def approve(self, change_id: str, actor: str) -> None:
        if actor in self.chain.actors(change_id, "author"):
            raise PermissionError(
                f"{actor} authored {change_id}; approval requires a second person")
        self.chain.append("approve", actor, change_id)

    def deploy(self, change_id: str, actor: str) -> dict:
        if not self.chain.actors(change_id, "approve"):
            raise PermissionError(f"{change_id} has no approval")
        if actor in self.chain.actors(change_id, "author"):
            raise PermissionError(f"{actor} authored {change_id}; cannot deploy it")
        return self.chain.append("deploy", actor, change_id)


if __name__ == "__main__":
    chain = ApprovalChain()
    gate = ReleaseGate(chain)

    gate.author("MODEL-2026-114", "r.khare")
    try:
        gate.approve("MODEL-2026-114", "r.khare")
        raise AssertionError("self-approval was permitted")
    except PermissionError:
        pass

    gate.approve("MODEL-2026-114", "a.controller")
    try:
        gate.deploy("MODEL-2026-114", "r.khare")
        raise AssertionError("author deployed their own change")
    except PermissionError:
        pass

    link = gate.deploy("MODEL-2026-114", "o.release")
    assert chain.verify(), "chain must verify after a legitimate sequence"
    assert link["action"] == "deploy"

    try:
        gate.deploy("MODEL-2026-999", "o.release")
        raise AssertionError("deployed an unapproved change")
    except PermissionError:
        pass

    # Tampering must be detectable, not merely discouraged.
    chain.links[1]["actor"] = "r.khare"
    assert not chain.verify(), "edited approval record still verified"

    print("SOX segregation of duties + approval chain: OK")
    print(f"  links {len(chain.links)}, verifies_after_tamper={chain.verify()}")

Risk mitigation matrix

Each row carries an acceptance parameter rather than an adjective, because "low latency" cannot be signed off. Retention here is bound by per the data class retention schedule, enforced automatically.

Review questions and answers

• Reproduce last quarter's figure exactly, using the model version that produced it.
  Version, prompt digest and output digest are recorded per reporting-relevant inference, and versions are pinned per period, so the figure is reproducible on demand.
• What function decides which destination may see RESTRICTED data, and where does it run?
  The routing gate, evaluated before egress. It is a deterministic function of the data's classification and the destination's attested properties, and it fails closed when no destination is lawful.
• Show me the recorded reason for a denial last week.
  Every allow and every deny is written to the decision log with the reason — which destinations were rejected and on which property — so a denial is explainable months later.
• When a document is embedded, does the embedding carry its classification — and is that enforced on read?
  Yes. The classification tag propagates into every derived store, including embeddings, caches and eval sets, and is enforced on read as well as write.
• What happens when a provider adds a subprocessor you have not disclosed?
  The drift detector alerts when a destination's attested properties change, and routing is re-evaluated against the new attestation. Attestations are versioned data, not a one-off questionnaire.
• How do you prove processing stayed in the contracted region?
  The provider endpoint is pinned per region and the served region is asserted on the response; a mismatch fails the request rather than completing it quietly.

Related architectures

• Part of enterprise ai data governance.
• Where this interacts with another regime, see fedRAMP Moderate data governance framework for enterprise LLM deployment.
• For the related constraint, see ISO/IEC 27001:2022 data governance framework for enterprise LLM deployment.
• SOC 2 Type II data governance framework for enterprise LLM deployment applies the same mechanism under a different obligation.
• For the related constraint, see EU AI Act data governance framework for enterprise LLM deployment.
• If this is the blocker in front of you: enterprise AI infrastructure review.