Audit & Compliance

Answer the auditor with a query

Every definition in the estate carries an owner, a version history, and a policy applied where the data is used. What a metric meant on a given date is a question the system answers directly.

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Key capabilities

Built for SOX, GDPR, BCBS 239, CSRD, and emerging AI governance mandates

Every change logged, attributed, timestamped, and reversible

Policy applied at the point of use, across the estate

Nearly 30 years of OEM metadata engineering

The Problem

Every audit cycle turns into a project

Metric definitions get reconstructed from tribal knowledge, job logs, and email threads. The regulator asks when a field changed, who approved it, and what it meant at the time of a specific transaction.

Answering that means pulling threads across systems that don't share a data model, so teams assemble the documentation by hand before every audit window.

SOX, GDPR, BCBS 239, CSRD, and the AI governance mandates now arriving all ask for evidence the estate can't produce on demand.

The Approach

Put the whole metadata estate under version control

Lineage, catalog entries, governance policies, and semantic definitions all sit under version and configuration management. Every change is logged, attributed, timestamped, and reversible.

Policy applied where the data is used, versioned where it changed. The record of enforcement and the enforcement itself are one system.

Audit readiness shifts from a sprint before the auditor arrives to a permanent state of the estate.

The audit answer is a query.

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What Changes

The answer on any date

What a metric meant, who changed it, and where it flowed, at any point in the history.

Enforcement with a record

Every definition can defend itself.

One answer for the board

The number in the board deck and the number in the financial system come from the same governed definition.

Fix business logic at the foundation

MetaKarta establishes the shared metadata foundation organizations have been trying to patch together for years: trusted BI, reliable AI, and defensible governance, compiled into every architecture, every cloud, and every tool. No runtime dependency. No vendor lock-in. No greenfield start required.

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Frequently asked
questions

Which regulations does this support?

SOX, GDPR, BCBS 239, CSRD, and the AI governance mandates now arriving all ask for similar evidence: where a number came from, who changed its definition, and whether policy applied where the data was used. MetaKarta keeps that evidence current, so it's ready whenever the request comes. Your auditors and counsel still make the compliance determination.

What can we show an auditor about a single metric?

What it meant on any date, who changed it, when, and which systems it flowed through, with column-level lineage from the source to the report. The auditor's question becomes a query against the record the system already keeps.

How is policy enforcement recorded?

Policies apply where the data is used and are versioned where they change, so the enforcement and the record of it come from one system. Security policies defined once compile into native row-level controls in each target platform.

Can we undo a change that shouldn't have happened?

Every change to lineage, catalog entries, policies, and definitions is logged, attributed, timestamped, and reversible. You can restore any historical point and show exactly what changed in between.

How does this help when the board asks about a number?

The figure in the board deck and the figure in the financial system come from the same governed definition, with lineage connecting them. When a director asks where a number came from, the trace already exists.

Does the audit trail cover AI outputs?

For agents grounded through MetaKarta, yes. Each answer traces from the response through the governed definition back to the source column, and every response returns the metadata evidence behind it, which gives an AI governance review the same kind of trail financial reporting already requires.

We already run a governance program. What changes?

The program keeps its policies, stewards, and glossary. It gains evidence: enforcement recorded where the data is used, and coverage computed from the estate itself, so the program can answer auditors and AI reviews on demand.