ClickHouse and EU AI Act Technical Documentation

Assessing how ClickHouse supports each Annex IV documentation aspect under the EU AI Act and identifying the missing gaps.

Tags: clickhouse eu-ai-act technical-documentation compliance rag

ClickHouse and EU AI Act Technical Documentation

tl;dr Assessing how ClickHouse supports each Annex IV documentation aspect under the EU AI Act and identifying the missing gaps.

ClickHouse GitHub Repository

Coverage matrix

Aspect	EU AI Act reference	ClickHouse support	Notes
System description & intended purpose	Annex IV (a)	partial	Store Markdown/PDF blobs or URLs; authoring, version control and approvals in Git/Confluence/DMS.
Design & architecture incl. algorithms	Annex IV (b)	partial	Metadata tables OK; diagrams and code history still need external SCM.
Data sets & governance metadata	Annex IV (c), Art 10	yes	Columnar tables track lineage; S3/Azure functions read raw samples; populate via ETL.
Performance metrics & test results	Annex IV (d)	yes	Write eval metrics to MergeTree tables; dashboards via Grafana/CH queries.
Risk‑management records	Art 9, Annex IV (e)	partial	Risk register can be a table, but workflow, review sign‑off and mitigation docs stay outside.
Human‑oversight description	Annex IV (f), Art 14	partial	Narrative oversight procedures stored as blobs; enforcement lives in Policy/OPS tools.
Post‑market monitoring & incidents	Art 15	yes	High‑volume logs → materialized‑view alerts; retains ≥10 y with tiered storage.
Automatic event logging	Art 12	yes	system.query_log, system.trace_log, custom tables satisfy lifetime traceability.
Cyber‑security evidence	Art 15	yes	Store audit logs (ClickHouse Cloud Audit tab) and security events for forensic replay.
Versioning & change history	Annex IV (h)	partial	Retention handled; true diff/merge & signed releases require Git/MLflow/OCI registry.

Key gaps

Authoring & lifecycle management of narrative documents – use Git‑based docs or DMS.
Electronic signatures / approval workflows – integrate QMS or e‑sign platform.
Automated generation of the Declaration of Conformity & Annex IV bundle – templating pipeline (e.g., Jinja + CI) that pulls metrics from ClickHouse and docs from Git.
End‑to‑end lineage across data, model, code – store hashes/IDs in ClickHouse but track artefacts in MLflow + OpenLineage.

Recommended compliance stack

ClickHouse – structured logs, metrics, lineage columns.
Git + Markdown/Asciidoc – narrative documents under version control.
MLflow or equivalent – model registry and artefact storage.
Quality Management System (QMS) – risk workflow, approval signatures.
CI/CD pipeline – automate Annex IV package assembly and DoC generation.

Conclusion

ClickHouse excels at high‑volume logging, metrics, and traceability required by the EU AI Act, but needs complementary tooling for narrative documentation, signatures, and artefact governance. Combine it with Git, MLflow, and a QMS to achieve full compliance while keeping analytics fast and cost‑efficient.