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GOVERNANCE ENGINEERING

What is Governance Engineering?

The practice of applying software engineering principles and tools to automate and improve the governance of software delivery.

The practice

Engineer the controls, don't automate the paperwork.

Governance Engineering is what happens when engineers design risk controls. Not faster forms. Real controls.

Design controls as software products.

Manual controls are tickets, documents, and trust. An engineered control is code: versioned, tested, owned, and observable.

Automate Enforcement.

Compliance happens in objective and provable decisions, not in a meeting weeks later. The compliant path is the fast path.

Never automate the tickets.

Faster paperwork is actively worse: risks aren't mitigated, they're accelerated. Engineer the control, not the receipt.

Event Context Evaluate Evidence Rules Decision Result Triggers Produces Get facts Uses /
An automated control: an event triggers an evaluation of rules against trusted facts, producing a recorded decision.

What it is not

A GRC tool

Off the shelf GRC tools can provide a fast path to SOC2 compliance, but Governance Engineering is the practice where engineers design and operate complex enterprise controls.

Ticket automation

Automating yesterday's broken processes with generated database rows is a risk accelerator and control anti-pattern this practice corrects.

A technology solution

Like DevOps and SRE, Governance Engineering is more about overcoming established silos and ways of working than any particular tool or technology.

The outcome

Continuous Compliance delivered in practice.

When controls are engineered, compliance stops being a periodic project and becomes a property of the system.

01 02 03 04 Policy Control Evidence Audit obligations expressed as intent automatically enforced recorded at source automated assurance CONTINUOUS Compliance

Always audit-ready.

Compliance is provable at any moment, as of any date. Every audit is a green tick instead of a scramble.

Zero marginal cost.

The 10,000th change is governed as cheaply as the first. Governance throughput scales with delivery.

Better risk control.

Every change evaluated against every policy, every time. Humans look only at what genuinely needs judgment.

Governance Infrastructure

Your Governance Infrastructure Architecture.

The practice needs an infrastructure platform comprising four layers. The layers in the stack connect data through relationships and entities.

04

Insight

Provide insight into how the SDLC and its controls are actually performing.

03

Audit

Demonstrate assurance to auditors, regulators, customers, and the board, continuously and as of any point in time.

02

Control

Express and apply policy as controls, mapped to the evidence that satisfies them, operated automatically.

01

Evidence

Record trusted facts from across the SDLC, in a form that can be queried and connected.

This is what Kosli provides.

See how it works
The problem

Tackle the last manual step in software delivery.

You automated build, test, and deploy years ago. Governance still runs on forms, meetings, and screenshots. Everyone pays: engineers in toil and delays, security in poor risk control, audit in cost and findings.

Automated

Code

minutes

Test

minutes

Deploy

minutes

Still manual

Governance

days to weeks

Evidence

Before

Screenshots, tickets, and exports, assembled by hand.

After

Captured automatically at the point of action.

Controls

Before

Policy documents, enforced by meetings. Over 90% of changes rubber stamped.

After

Automatic policy enforcement and evidence.

Audit

Before

Expensive, retrospective, time consuming and sampled.

After

Continuous assurance over every event

The FCA analyzed over 1M production changes and found manual governance correlates with worse outcomes. DORA research shows formal CAB approval makes low performance 2.6x more likely. And regulation (EU DORA, NIS2) already expects continuous, defensible evidence. It is time to act.

AI is disrupting traditional governance

Enable governance to scale to agentic change rates.

Change volume Manual governance capacity capacity reached Lost productivity Quarterly releases DevOps · 100× Agent swarms · 10,000×
Illustrative.

Design governance for the AI tidal wave

Traditional paperwork designed for quarterly releases won't cut it.

Eliminate manual approval bottlenecks

Build safety and auditability into every control

Audit every change in real time

Go from retrospective and sampled control testing to automated reconciliation

The Control Group

Want to learn more? Join the club.

Governance Engineering is being defined in the open: in the FINOS SDLC Common Controls Working Group, in the Controls Engineering book, and in The Control Group, our community for engineering leaders in regulated industries.

Come compare notes with the practitioners doing this work at the world's largest banks.

Join The Control Group
Controls engineering

Learn how to turn governance into code.

Controls Engineering applies modern software engineering practices, requirements, testing, automation, observability, to the controls that govern software delivery. A control becomes a software product, not a paperwork exercise.

DevOps applied software engineering to operations. SRE applied it to reliability. Controls Engineering applies it to governance.

Download the Guide to Controls Engineering
Controls Engineering — book cover
Get started

Start engineering
your governance.

Read the guide the practitioners wrote, or talk to the team shaping the practice.

Watch it work, end to end

See the platform enterprise teams use to automate governance across build, release, and runtime.

Kosli in action