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AI governance for software delivery

Governance is the product.

Not a feature. Not a PDF. The thing you are buying.

What does it mean to govern AI-generated software?

Governing AI-generated software means every change can answer four questions:

  1. Which business goal ordered it?
  2. Which policies was it checked against?
  3. Who and what produced it?
  4. What evidence supports deploying it?

If an answer is missing, the gate shows it, before production instead of after.

The readiness gate

22 checks. The bar production sets.

The gate is the readiness bar for regulated software: what production demands before anything ships. The factory's job is to produce the evidence, check by check. An ungoverned change scores 0 of 22. That is not an insult. That is normal, and it is the problem.

Govern5

  • DPIA
  • Threat model
  • Audit log
  • Change control
  • EU AI Act evidence

Secure5

  • Security hardening
  • IAM
  • Secrets and keys
  • Threat detection
  • GDPR and data residency

Build5

  • Integrations (ERP, IdP)
  • Documentation
  • Testing and QA
  • Infra as code
  • CI/CD and rollback

Run7

  • Observability
  • Logging
  • Incident response and on-call
  • SLOs and error budgets
  • SBOM and patching
  • Backup and DR
  • High availability

Where the evidence comes from

A check you cannot evidence is a checkbox. Each family draws its evidence from a different part of the factory, and every line of it lands in the audit trail below.

  • Governthe Learn document set and the decision chain, from the business goal that ordered the work to the merge that closed it.
  • Securehardening and scanning in every build, plus the Operate sweep after the change ships. Production threat detection for delivered systems is on the roadmap.
  • Buildthe implementation package: infrastructure as code, CI/CD pipelines, and as-built documentation.
  • Runresilience evidence delivered with the project. Observability, incident response, and deployment orchestration are on the roadmap, and we say so.

Score your last project against these. Take the self-test

The long answers: governance debt and the 2027 deadlinewhat the research says about AI-written codethe off switch is not governance

Policy as code

Your policies, enforced where the work happens.

Most companies keep policies in documents that agents never read. Taiga turns policies into machine-readable rules enforced as the agents work, not audited after the fact: they shape the specification, the plan, and every build, and the record proves it. Overrides exist for the cases that need a human call, and every override is recorded with a name on it.

One policy, four stages

A policy you publish in Taiga is not a reference document. It does work at every stage of a project:

Requirements and specs
Policies feed intake and document generation, so the specification, data classification, threat model, and DPIA are produced against your standards from the first draft.
Planning
Policies and standards inform the backlog and the acceptance criteria, so compliance and hardening work is planned in from the start.
Building
Every build runs security hardening and scanning, and follows your architecture and development standards, before a pull request opens.
Maintaining
Your dependency and supply-chain policy sets the bar for what gets flagged and what gets fixed after the software ships, so maintenance answers to the same standards as the build.

Set policy once. Every project inherits it.

Where each stage runs in the factory

Policy and standards areas

  • Security
  • Data protection
  • Software development lifecycle (SDLC)
  • Operations
  • Risk
  • Architecture
  • Supply chain
  • Cloud governance
  • Acceptable use
  • Intellectual property

Alongside your design standards, brand standards, and business goals.

Fig. 01 · Policy engineCompany policies, versioned and tailored to the organization, applied as the work is created.

The audit trail

From business goal to deployed change, unbroken.

Every factory run records the chain: goal, purpose, outputs, activities, decisions, prompts, diffs, checks, deployment. Your auditors can read it without asking us for exports.

After every merge, Taiga rewrites the project's as-built documentation to match what actually shipped. Drift has nowhere to start.

Governance does not stop at merge

After a change ships, its dependencies are judged against your supply-chain policy rather than a generic severity feed. A finding closes only when the fix has been independently re-verified. Both the judgment and the verification land in the record as change-control evidence, the kind an auditor asks for and rarely gets. The trail that starts at the business goal keeps growing while the software runs: policy, decision, verification, all on the same chain.

The same bar applies to us: the platform's own audit logs sit in an immutable seven-year archive, available to your security team on request.

See the trust center

Who decides

Human oversight, on the record.

Every factory run has fixed points where a person, not an agent, decides. Each decision writes to the record:

  • A person approves every Learn document before anything is built from it.
  • Agent-drafted specifications and plans go live only when a person publishes them.
  • Every change arrives as a pull request that a person reviews and merges.
  • Every override carries the name of the person who made the call.
Fig. 02 · Your turnThe backlog knows whose move it is: start the build, retry it, or review the pull request. A person decides, and the record shows it.

When the EU AI Act row in the table below names human oversight points, this is what it points to. Not a diagram of intended oversight: a record of oversight that happened. Auditors do not have to take anyone's word for where the humans were.

What regulators ask, what the factory produces

GDPR
DPIA, data flow maps, and records of processing, produced in the Learn loop and approved by a person before build
NIS2
risk register written before build, continuous supply-chain posture, incident-ready audit trail
DORA
traceability from initiative to pull request, dependency posture judged against your supply-chain policy
EU AI Act
documented model use, human oversight points on the record, decision logs
MDR
the chain from specification to verification evidence, linked at every step
NESA and national frameworks
deployment in your environment, EU-only inference, revocable code custody

Taiga produces the artifacts and the evidence. Certification and regulatory assessment remain your process, and your auditors stay in charge. We make their job boring.

Under the EU AI Act, the provider or deployer of the delivered system is you. Taiga is a tool vendor in your supply chain, and the factory produces the evidence your conformity file needs.

How this maps to your vertical

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Paying customers in healthcare and fintech run on this today.

Score your last project. /gateThe security answers behind all of this