Governance is built into the work, not added afterwards.

Governance starts with understanding the actual workflow: the decisions that are made, the data that is used, the exceptions that occur, the owners who are accountable and the risks that matter. Only after that does it make sense to recommend AI, automation or any other technology.

A poorly understood process will produce a poorly governed outcome — regardless of how sophisticated the model is.

Where personal data is involved, processing is purpose-led and minimised. Reveloris assesses the appropriate legal basis, access, retention and data-subject rights for each context, and documents them as part of the engagement.

For the website Privacy Policy — including what is collected through the inquiry form, how it is stored, who processes it and how to exercise your rights — see reveloris.com/privacy.

reveloris.com uses no analytics service, no advertising or profiling cookies, no tracking pixels, no advertising tags and no social media trackers. Nothing is stored on your device and visitors are not tracked across websites.

Because nothing non-essential is stored on your device, no cookie consent banner is required or shown.

If privacy-friendly measurement or any non-essential tracking is introduced in the future, the Privacy Policy and this page will be updated and appropriate consent and transparency controls will be implemented before any tracking begins.

AI use cases should be assessed according to the role the AI plays, the risk it creates and the regulatory environment in which it operates. That includes identifying whether a use case is prohibited, high-risk or subject to transparency obligations, and ensuring the required documentation, risk management and human oversight are in place.

This is an engagement discipline, not a certification. Reveloris does not state that any particular system, customer deployment or service is “EU AI Act compliant.” Applicability depends on the specific system, role and use case.

AI should not remove accountable human ownership where judgement, consequence, regulation or risk requires it. Controls and escalation paths are designed around the actual workflow, so it is clear who decides, who reviews and who is accountable when the model is uncertain or wrong.

Oversight is treated as part of the process design, not as a layer added after the model is built.

Reveloris applies the following principles to client and engagement data: data minimisation, appropriate access control, careful handling of client information, clear separation between client environments, and proportionate security controls matched to the sensitivity of the work.

For the public website, technical measures include encrypted connections, access-controlled database storage, rate limiting on the inquiry form and restricted access to submitted data. These are controls, not guarantees: no online service can be completely secure, and this page makes no certification or absolute security claim.

Solutions may use external AI, cloud, automation or infrastructure providers. The role of each provider, how it handles data, the contractual terms that apply and its suitability for the engagement are assessed as part of the design — not assumed.

Reveloris does not own or operate the underlying third-party models or platforms. Responsibility for selecting, configuring and governing them is allocated clearly between Reveloris and the customer.

Governance must be adapted to the customer’s actual regulatory environment. GDPR and the EU AI Act may be relevant, and sector-specific regimes may also apply. For financial-sector contexts, for example, the Digital Operational Resilience Act (DORA) may be a consideration for ICT risk management and third-party risk.

These references are not blanket compliance claims. Reveloris does not state that it, or any customer deployment, is “DORA compliant,” “GDPR compliant” or certified under any regime unless a specific, verified engagement conclusion has been reached and documented.

Reveloris works from the principle that impact is measured, not asserted. Baselines, decision criteria, controls and evidence are defined so that outcomes can be reviewed rather than simply claimed.

Auditability is designed in from the diagnosis: what was assumed, what was tested, what changed, what did not change, and what the organisation should watch after go-live.

For privacy and data-protection matters: privacy@reveloris.com.

For general governance and client questions: hello@reveloris.com.

Last updated: 19 August 2026