Reference implementation, dated 2026-07-11. A good-faith classification of this system under Regulation (EU) 2024/1689 (the EU AI Act), written because a European public body — or a US agency benchmarking against the strictest available framework — would ask for one. It is an engineering assessment, not legal advice.
This system, as designed, is not high-risk. It is a limited-/minimal-risk information tool subject mainly to the Article 50 transparency obligation. The reason it stays out of the high-risk tier is the same design choice the whole project is built on: it does not evaluate anyone's eligibility. A variant that did would land squarely in Annex III, and that boundary is drawn deliberately.
Prohibited (Article 5). None apply. No social scoring, no biometric categorisation, no manipulation, no emotion inference.
High-risk (Article 6 + Annex III). The relevant entry is Annex III(5)(a): AI systems intended to be used by public authorities to evaluate the eligibility of natural persons for essential public benefits and services, or to grant, reduce, or revoke them.
This system is adjacent to that category and deliberately outside it:
- It explains published criteria ("the criteria are 65 and older") and routes the decision to the agency. It never outputs an eligibility determination about the individual asking.
- That line is enforced, not merely promised: an output guard blocks
determination language, every answer must cite the corpus, and a dedicated
refusal eval suite tests both. See
src/assistant/guards.pyandevals/suites/refusal.yaml. - It performs no profiling and makes no automated decision producing legal
or similarly significant effects on a person (also the Article 22 GDPR line;
see
docs/dpia.md).
Because the system does not evaluate eligibility and is not used to grant or reduce a benefit, Annex III(5)(a) is not triggered. The design keeps the human/agency as the decision-maker and positions the tool as published-policy retrieval, not adjudication.
The boundary, stated plainly. If this were changed to tell a rider whether they qualify, or to issue or deny a reduced-fare credential, it would become a high-risk system under Annex III(5)(a), pulling in Article 9–15 obligations (risk management, data governance, logging, human oversight, accuracy/robustness documentation). The project treats "never determine eligibility" as the architectural invariant that holds it below that line.
Limited risk (Article 50 — transparency). This is where the system sits. It interacts with natural persons, so users must be informed they are dealing with AI. That obligation is met: the live page opens with a "reference implementation" banner stating it is an AI demonstration and not an official agency service, the "will not do" list is shown before the input, and every answer is dated and cited.
Minimal risk. The remainder of the system's behaviour (information retrieval over public documents) falls here, with no additional obligations.
The system uses a general-purpose model (Claude) via a provider, not a first-party GPAI model placed on the market, so the GPAI-provider obligations (Article 51+) fall on the model provider, not this deployer.
Even at limited risk, an agency putting this in front of real riders should keep
the Article 50 disclosure prominent, maintain the DPIA and the AI risk register
(docs/dpia.md, docs/ai-risk-register.md), and re-classify if the scope ever
moves toward eligibility decisions. The classification is only as durable as the
no-determination invariant, which is why that invariant is guarded in code and
tested, not left to the prompt.