The market had cataloguers, classifiers, and policy documenters. What it did not have was an enforcement layer — a platform that produces continuous, independently verifiable evidence without ever touching your underlying data.
The market had cataloguers, classifiers, and policy documenters. What it did not have was an enforcement layer — a system that proves governance is happening at the moment it matters, with a full audit trail that withstands regulatory scrutiny.
That is what Main-Abe builds. A platform that produces continuously generated, independently verifiable compliance evidence — automatically, at the moment it matters — without ever touching your underlying data.
Every capability below is built on the same discipline: produce evidence automatically, never touch customer data, speak the language of regulators and the CFO.
Most executive teams discover their compliance posture from a slide deck assembled by a compliance officer in the week before the board meeting. By the time the board reads it, the underlying data has already moved on.
The Executive Dashboard is built for the moment a Chief Risk Officer, an Audit Committee chair, or a regulator asks the simple question: "How are we doing?" The answer arrives without a project plan, without a deck preparation, and without a stale snapshot. The dashboard is one continuously-refreshed surface — compliance score across all data movements, total records under governance, open issues by severity, and a twelve-month trend.
Every number is traceable. Click a metric, and the dashboard drills into the underlying signals — the contracts that produced it, the regulations involved, the owners responsible. Nothing on the dashboard is opinion. Everything is evidence.
A regulated financial services firm we briefed in Q1 2026 estimated the Executive Dashboard would replace forty-eight hours of compliance-team work per quarter — the time historically spent assembling, reconciling, and presenting the board's compliance update. With the dashboard, that update is available on demand and is always current.
Most governance programmes are evaluated by the consultant who designed them. That conversation happens once a year, in a slide deck, in a board room. Governance Health is the alternative.
A continuously-updated measurement surface tracks how the governance programme is actually performing — across the four dimensions that matter to a regulator and to the executive team: contract coverage of the data estate, regulation coverage across the obligations that apply, issue resolution within service-level targets, and evidence completeness across every contract.
The score is not a self-assessment. It is a calculation derived from the same telemetry that drives every other capability on the platform. If the data behaves, the programme is healthy. If it does not, the programme score reflects that, immediately.
A traditional consultancy maturity assessment costs six figures and produces a recommendation that is twelve months out of date by the time the next annual review begins. Governance Health turns the assessment into a continuously-running calculation that any internal stakeholder can read on demand — without scheduling a workshop or signing a fresh statement of work.
Most compliance issue lists are spreadsheets. Spreadsheets are written; they are not updated. A list written a week ago describes a state of the world a week ago, not the state of the world right now.
Governance Readiness is the live, continuously-tracked queue of every active compliance issue, every owner, every regulatory tag, every age. Issues are detected the moment a contract check fails. They are classified by severity. They are routed to the named human owner accountable for resolving them. They are tracked through the lifecycle until evidence of resolution is recorded.
For a Chief Compliance Officer preparing for a regulator visit, the list answers the question every regulator asks first: "What do you know about right now, who owns it, and when will it be fixed?" The answer is on screen, current to the minute, before the regulator finishes the question.
In financial services supervision, the most consequential conversations begin with a regulator asking a Chief Compliance Officer to walk through their current open issues. Governance Readiness is built for that moment — a triage surface where every active issue, every owner, every regulatory tag is always current. No "let me check with the team and get back to you."
Traditional maturity models are scored by interview. Three consultants ask twelve questions of nine senior leaders and write a number on a slide. The number is a story, not a measurement.
The Automated Maturity Model derives its score from what the data is actually doing — every pipeline run, every contract check, every signal raised, every resolution recorded. The five rungs are the standard industry ladder (Initial, Repeatable, Defined, Managed, Optimised), but the position on the ladder is calculated, not asserted.
The trajectory is shown alongside the current position — where the programme is today, and where it is projected to be in twelve months on the current rate of governance maturation. For an executive team building a multi-year compliance roadmap, the model replaces the consultant's recommendation with the platform's own measurement.
When a CFO asks the Chief Compliance Officer to justify next year's compliance budget, the conversation usually rests on a maturity-assessment narrative. With the Automated Maturity Model, the conversation rests on a measurement. "We were at Level 2 a year ago, we are at Level 3 today, and the trajectory has us at Level 4 inside the next budget year — here is the evidence."
A traditional audit produces evidence at a point in time. A regulator with a question about something that happened six months ago has to wait while a team reconstructs the answer from logs that may or may not exist.
Evidence Records is the continuous, independently verifiable record of every compliance check that has ever run on every contract — the proof that governance was operating at the moment it mattered. Each entry is time-stamped and linked to the regulation it supports. The record is not assembled retrospectively when an auditor asks for it. It is built continuously, in the moment, automatically.
For a regulator asking a question about compliance behaviour at a specific point in the past, the answer is retrievable on demand. The evidence is not a story constructed after the fact. It is the artefact that was produced when the data moved.
Internal Audit teams typically scope a compliance audit as a multi-month engagement — fieldwork, sampling, interviews, evidence reconstruction. With Evidence Records as the standing source of truth, the question shifts from "can we produce the evidence?" to "which slice of the evidence do you want to see?" The audit becomes a query, not a project.
The hardest question in data governance is the one most programmes cannot answer: what is in our estate that we are not governing? A governance programme that only knows about the data it has chosen to govern is a programme that cannot answer that question.
Estate Governance Visibility is the continuously-updated coverage measurement across the entire data estate — what is governed, what is not, where the gaps are, and which gaps have owners. The coverage is shown as a single number for the executive team and as a domain-by-domain breakdown for the people responsible for closing the gaps.
Every gap is named. Every gap has an owner. Every gap is scheduled. The dashboard does not present a network or an architecture diagram; it presents the answer to the question the regulator will eventually ask: "What in your estate is not under governance?"
In every enterprise we have worked with, the first scan of the data estate has surfaced data assets that the central governance programme did not know existed — quarter-end spreadsheets, marketing analytics warehouses, partner data feeds. Estate Governance Visibility makes that conversation a routine one rather than a project. The shadow estate is named, owned, and scheduled.
A data contract is the formal agreement between a data producer and the consumers who depend on the data. It describes what the data must contain, how it is verified, what regulatory obligations apply, and what service expectations the consumers can rely on.
On the platform, a contract is a four-part artefact: schema (the structure the data must take), validation rules (the conditions the data must satisfy), sensitive-field tags (the regulatory obligations that apply), and service expectations (freshness, availability, completeness). Defining a contract is the act that turns ungoverned data into governed data — and the platform enforces every contract on every data movement, automatically, from the moment the contract is signed.
Every contract is linked to the policies and regulations it supports. The contract is not a document filed away; it is a live enforcement instrument. When the regulation changes, the obligation surface for the contract changes with it.
A traditional governance programme defines policy at the enterprise level and hopes for adoption at the team level. The data contract inverts that direction — every team owns the contracts for the data they produce, every contract carries its own enforcement, and every enterprise-level policy is the sum of the contracts that operationalise it. The unit of governance shifts from the policy document to the data contract.
The right to erasure is the right an individual has to require an organisation to delete their personal data. It is one of the most consequential rights in modern data law — and one of the easiest for an organisation to mishandle without realising.
Governed Deletion handles the lifecycle from request received to audit trail entry. Stage one identifies the subject. Stage two performs the impact analysis — every system, every record, every linkage that touches the subject's data. Stage three executes the deletion across every identified target. Stage four records the proof: the regulator-ready audit trail entry that the request was received, the scope was correctly identified, the deletion was performed, and the verification confirmed it.
For a Data Protection Officer, the value is the evidence that the right was honoured correctly — not the operational confidence that someone clicked a button somewhere. The proof is the artefact, recorded continuously, retrievable on demand. The deletion is not the end of the story; the evidence is.
Different jurisdictions impose different timelines, different scope rules, and different evidence requirements for erasure requests. Governed Deletion is the same lifecycle for every regulation — the regulation determines the scope and the timeline; the platform produces the evidence. A multi-jurisdictional organisation sees one workflow and one evidence model, not a patchwork of regional procedures.
The platform operates as an independent layer alongside your pipelines. It produces evidence without extracting, copying, or transmitting your underlying data. Your pipelines never slow down. Your data residency obligations are preserved. Your security posture is not widened by the platform's presence.
The same platform, deployed identically across the three major cloud providers — without bespoke modifications for each environment. Multi-cloud organisations get consistent governance coverage. Single-cloud organisations get portability if they ever need it. The platform adapts to your cloud choice; you never adapt to the platform's.
Three lines that explain exactly what makes Main-Abe different from every other governance tool.