API Documentation

Returns a list of findings for your organization.

Required scope: findings:read

Query parameters

Returns a list of assessments for your organization.

Required scope: assessments:read

Query parameters

Returns a list of remediation tasks linked to your organization's findings.

Required scope: remediation:read

Query parameters

Read and update evidence metadata (filename, type, size, description, review/expiry dates, version). File contents are never served or writable via the API.

• GET — list evidence metadata (evidence:read).
• PATCH — update metadata by id (evidence:write). Writable: description, review_date, expires_at only.

Query parameters (GET)

Read and manage vendors, including the AI each supplies (ai_involvement), whether it trains on your data (customer_data_training), agreement status (has_agreement, agreement_signed_at, agreement_expires_at) and review dates. Pass ?id= to GET a single vendor.

• GET — list or fetch vendors (vendors:read).
• POST — create a vendor (vendors:write). Body: name (required), plus optional contact_name, contact_email, website, services_provided, data_access, risk_level, status, has_agreement, agreement_signed_at, agreement_expires_at, ai_involvement, customer_data_training, next_review_date, notes. Returns HTTP 201.
• PATCH — update a vendor by id (vendors:write).

Query parameters (GET)

The AI system registry. GET lists systems (filters stage, risk_tier, generative, q) or fetches one with ?id=, adding its intended use, oversight design and models (ai_systems:read). POST proposes a system (ai_systems:write): it is created in proposed, unclassified, and counts toward your system cap. The API never decides: a request carrying risk_tier, eu_ai_act_class, is_gpai, lifecycle_stage or next_review_date is refused. A person sets those on the system's page, and the lifecycle moves only through a review.

Filters take the listed values only; any other value is refused with HTTP 400, naming the allowed values.

AI models (models:read). ?id= returns one model with its recorded versions, the systems it backs and how many evaluation results exist.

Register a new version of a model from a CI or ML pipeline (models:write). Body: model_id, version (required), optional released_on, evaluation_summary, notes. It changes no system's approval; a system that pins a version keeps its pin.

Model evaluation results, one metric per result. GET ?model_id= (optional version_id) lists them newest first, paged with limit (at most 200) and offset (models:read). POST records one (evaluations:write, not granted by default): model_id, version_id, metric, value, optional threshold, passed, dataset, notes, measured_at. Results are append-only, and passed is recorded as sent, never worked out from the threshold.

Published model and system card versions (cards:read). Pass version_id, or system_id / model_id for that subject's latest published card with its content. Drafts are never returned.

AI system reviews and the decisions approvers signed (approvals:read). Filter by system_id or status; ?id= returns one review with its approvers and decisions. Read-only: a decision is signed in the dashboard with a password and a second factor, never through a key.

Filters take the listed values only; any other value is refused with HTTP 400, naming the allowed values.

The AI risk register. GET lists risks (filters status, category, treatment, ai_system_id) or fetches one with its treating controls (risk_register:read). POST creates a risk (risk_register:write, org admins only) under the same rules as the form: the trustworthy characteristic is required, a NIST AI 600-1 category needs a generative system or model, and the residual pair is both or neither. Unrated residual values are null, never zero.

Filters take the listed values only; any other value is refused with HTTP 400, naming the allowed values.

Manage the delivered-training employee roster — built for HR-system sync. Employees are keyed by email (unique per organization), so re-posting a person updates them and never duplicates. Course assignment and invite emails stay in the dashboard.

• GET — list the roster, ?id= for one employee, ?active=1 for active only (training:read).
• POST — upsert by email (training:write). Body: full_name (required), email (required), optional department and ai_roles, a list drawn from builder, reviewer (approvers) and executive (leadership); everyone takes AI literacy and each role adds its own course. Returns HTTP 201 when created, 200 when an existing email was updated.
• PATCH — update by id: full_name, department, is_active (training:write). Deactivation excludes the employee from bulk assignment while preserving history.
• DELETE — remove by ?id= (training:write). Employees with completed training cannot be deleted (HTTP 409) — completions are compliance evidence; deactivate instead.

Read-only delivered-training report (training:read): every assignment with its effective status (expired once a pass is older than the 12-month validity window), score, attempts, duration, valid-through date, reminder count, invite-failure flag, and certificate id, plus an org-level stats block. Filters: course_key, status, employee_id; paginate with limit/offset. Assigning, resending, and revoking are dashboard-only actions (they send email).

The complete merged training transcript (training:read) — both delivered employee training and legacy manually-logged completions, the same dataset as the dashboard transcript export. One call gives an auditor or HR system the organization's full training record. Filters: q (person name/email), source (delivered|logged), status; paginate with limit (max 200) / offset. Every pull is recorded in the audit log.

Manage your organization's outbound webhook endpoints.

• GET — list endpoints (webhooks:read). Append ?catalog=1 for the list of subscribable event names. Signing secrets are never returned on read.
• POST — create an endpoint (webhooks:write). Body: url, events (array), optional description. The signing secret is returned once in the response.
• PATCH — update url / events / description / is_active by id (webhooks:write).
• DELETE — remove an endpoint by id (webhooks:write).

Webhook URLs are validated against an SSRF guard. Use the X-HTTP-Method-Override header if your client can't send PATCH/DELETE.

Returns AI incidents for your organization: type, severity, the AI system and model involved, whether personal data was involved, people affected (null when not yet known), and whether the incident is serious and when an authority was notified. Pass ?id= for a single incident. POST creates one (incidents:write) with title, discovery_date and optional incident_type, severity, ai_system_id, ai_model_id, description, personal_data_involved, people_affected, serious_incident. A new incident starts open; move it on in the dashboard once it has been triaged.

Required scope: incidents:read

Query parameters

Returns policies with status, version, owner, and review dates. Pass ?id= for a single policy.

Required scope: policies:read

Query parameters

Returns your organization's tamper-evident audit log, newest first — the same event stream that drives webhooks and SIEM export. Ideal for pulling activity into your own SIEM/GRC tooling.

Required scope: audit:read

Query parameters

Returns your organization's current compliance score (0–100), letter grade, and the per-dimension breakdown (Findings, Policies & Docs, Training, Incident Response), plus the date of the last daily snapshot.

Required scope: compliance:read