Haakon & Haakon™ is legal-reasoning software from Fjell Systems AS, built for the person with the problem — not for the institution on the other side of it. On our assessment it is not a high-risk system under Annex III of the EU AI Act (Regulation (EU) 2024/1689): that Annex is a closed list, and the entries that come closest cover systems operated by or on behalf of courts and public authorities. Ours is operated by the individual.
We hold ourselves to the Chapter III requirements anyway, as voluntary alignment — because they are what a careful product does with someone's legal situation, not because we are compelled to. This page states honestly where that stands, including what is not done.
| Obligation | What it requires | Status | Where we are |
|---|---|---|---|
| Art. 9 — Risk management | A continuous risk-management system across the lifecycle. | In progress | Two security audits worked off (both kill-chains closed); a formal, documented risk-management process is being structured. |
| Art. 10 — Data & data governance | Governance of training, validation and testing data sets. | Not applicable | Downgraded from “Compliant” on 30 July 2026 — it was answering a different question than the Article asks. Article 10 governs the training, validation and testing data of a high-risk system. We do not train, fine-tune or evaluate models on your case material: we send redacted text to a general-purpose model and keep the output. So most of Article 10 has no subject matter here, and claiming compliance with it credited us for work the Article does not ask of us. Our actual data-protection duties are live today under the GDPR, and they are stated in the next row rather than borrowed into this one. |
| GDPR Art. 5(1)(c) + Art. 25 — Data minimisation & protection by design | Process no more personal data than you need; build the safeguards in. | In progress | This is the honest home for the redaction promise, and unlike the AI Act it is in force in Norway now. Personal data is removed before case text reaches a model, and the pipeline refuses to run when the redactor is unavailable rather than proceeding unprotected. Case material is stored in Norway; redacted text is processed in the EU/EEA (Azure Data Zone). Two things stated plainly instead of an absolute: redaction is measured, not assumed — we publish recall figures rather than claiming perfection — and audio transcription reads the raw recording inside our own boundary before redaction applies. “In progress” because the default protection profile for documents is still being settled; this row gets its final wording when that decision lands. |
| Art. 11 + Annex IV — Technical documentation | A structured technical file describing the system. | In progress | The architecture is documented; formalising it into the Annex IV structure is in progress. |
| Art. 12 — Record-keeping (logging) | Automatic, tamper-evident logging of events over the system's lifetime. | In progress | Downgraded from “Compliant” on 30 July 2026, because the scope was wider than what we built. What exists is real: Vör-Log writes security-relevant events — access, authentication, role changes, redaction approvals — to a hash-chained, append-only trail, so any retroactive edit breaks the chain, and Vör-Report produces the record on demand. What Article 12 asks for is broader: traceability across the system's whole lifecycle, not only its security events. That gap is named here rather than hidden behind the part we did finish. |
| Art. 13 — Transparency & instructions | Users can interpret output; instructions for use are provided. | In progress | Output is structured guidance (not raw model text). Formal instructions-for-use are being written. |
| Art. 14 — Human oversight | Humans can understand, monitor, and override the system. | Compliant | The system never acts autonomously — every output is a draft the user reviews and confirms. A per-file human approval gate governs cloud processing; an adversarial review layer (Tyr) flags errors; users can correct any output; Vör logs oversight actions. |
| Art. 15 — Accuracy, robustness & cybersecurity | Appropriate accuracy, resilience, and security. | In progress | Fact-sheet anchoring constrains the model to verified values; security hardening shipped; Vör-Watch detects suspicious access. Formal accuracy metrics are still to be documented. |
| Art. 16–21 — Provider obligations & quality management | A quality-management system and provider duties. | In progress | Being formalised alongside the technical documentation. |
| Art. 43 / 47 / 48 — Conformity, declaration & CE marking | Self-assessment, a declaration of conformity, and CE marking. | Not applicable | These follow from a high-risk classification. On our assessment H&H is not an Annex III system, so there is no basis on which to affix a CE mark — and claiming one we are not entitled to would be worse than claiming none. |
| Art. 49 — EU database registration | Registration in the EU high-risk database before deployment. | Not applicable | The high-risk database is for high-risk providers; it is not something a system outside Annex III can usefully register in. |
| Art. 50 — Transparency (applies in the EU from 2 August 2026) | Telling people they are interacting with an AI system, and marking AI-generated content where that applies. | In progress | This is the one obligation on this page that goes live within days, and it was not deferred. To be precise about where it stands: it binds providers serving users in the EU from 2 August 2026. It is not yet binding in Norway, where the AI Act awaits incorporation into the EEA Agreement and a Norwegian implementing act. We treat it as binding from that date regardless. How we meet it: Freyja, the assistant you talk to in H&H, is an AI system with a name — not a person, and never presented as one. She says what she is when you first meet her, and a persistent line under the message box states it throughout every conversation, so the identification does not depend on remembering the first message. The wording is checked against the European Commission's guidelines of 20 July 2026 and written in Norwegian, not translated from a mockup. Beyond identification, nothing Freyja produces acts on its own. Every draft is reviewed and released by you before it counts, every document you share carries a line stating that AI was involved and who released it, and a letter you file in your own name stays visually yours — you are the author and the paper says so. On Article 50(2) — machine-readable marking of AI-generated content — we promised to publish a conclusion here either way, and here it is: the duty applies to us as the system's provider, and we meet it by marking rather than by arguing exemptions (position of 11 August 2026, revised 12 August, with counsel for confirmation). Concretely: the exported PDF letter will carry a machine-readable provenance note in its document metadata — recording that AI assisted the draft and a person reviewed and approved it — while the visible page stays entirely yours; and the AI-generated surfaces inside the product get a machine-readable layer to match their visible labels, built to the format of the Commission's Code of Practice on Transparency of AI-generated Content. The law gives this a deadline: the marking grace period ends 2 December 2026. This row stays “In progress” until both marks are shipped, not because the position is uncertain but because a status badge here describes what is built, not what is intended. |
| GDPR Art. 22 — Automated decision-making | A legal basis where a decision is solely automated. | Under legal review | Our reading is that Article 22 is probably not engaged: it governs decisions made about a person, and nothing here decides anything about you — the output is your own working material, aimed at the institution on the other side. We are saying “probably” rather than “no” because it is counsel's call and it has not been made yet. Mitigated meanwhile: every output is a non-binding draft until a human confirms it. |
| GDPR Art. 35 — Data protection impact assessment | A written DPIA where processing is likely to be high-risk to people. | In progress | Added to this page on 30 July 2026 because it was missing and should not have been. A DPIA is the instrument that most clearly applies to us: special-category data (health, family, immigration status) about people in vulnerable situations, at scale. It has not been written yet. It is owed before the pilot widens beyond invited users. |