AI-assisted generation
The AI suggests risk types, suppliers, processes, risks (including KRIs) and tasks in the context of industry, country, regulator and framework(s) — including from uploaded documents.
View on the platform →Feature catalog
The complete, filterable catalog of every Goveron feature, from guided structure setup through AI-assisted generation and risk scoring to evidence workflow, monitoring and reporting.
101 features across 18 areas
Core features
The AI suggests risk types, suppliers, processes, risks (including KRIs) and tasks in the context of industry, country, regulator and framework(s) — including from uploaded documents.
View on the platform →Every risk gets an inherent risk from likelihood × impact, plus a two-stage residual risk: pre-audit from the weighted completion level of its tasks, post-audit based only on accepted or auditor-confirmed evidence.
View on the platform →A piece of evidence moves through six clearly defined states — from upload and AI pre-review (accepted/rejected/inconclusive) to independent confirmation or rejection by the auditor.
View on the platform →Key risk indicators with a value and a target trigger an alert on threshold breach; external KYC and monitoring events additionally raise critical risk indicators and feed directly into risks, tasks and reports.
View on the platform →Every save writes its own immutable version with editor, timestamp and audit flag; when an auditor opens a project, the system automatically freezes the current state as a baseline.
View on the platform →A dashboard brings together metrics on departments, processes, risks, tasks, evidence and KRIs, complemented by exportable risk and department reports and a network graph running from department to supplier.
View on the platform →A company structure built once (industry, country, language, scope, suppliers, departments, processes) reused across many regulatory assessments.
An assessment of a company against one or more frameworks; framework-specific data lives exclusively on the project.
On creation, the company structure is deep-copied into the new project — later changes to the company never touch existing projects.
For example, one project each for GwG, ISO 27001 and DORA, all built on the same structure.
A central overview of "Your companies" + "Your projects" with create, open, export and delete.
An inline renameable project name, plus a way to switch back to the hub from the sidebar.
The project home maps the entire journey: Company · Project setup · Operations · Results — each row jumps straight to the matching step or report.
The board shows the next sensible step, or "all done," guiding you through setup and day-to-day work.
Industry → country → region → framework → risk types → suppliers → departments → processes → risks → tasks.
Company profiles run through 5 steps, projects all 10 — navigation and header adapt accordingly.
Multi-select via chips (ISO 27001, DORA, GDPR, GwG, GlüStV, AMLDs …), fuzzy-matched.
During company setup, Focused / Balanced / Broad plus a department slider control both the breadth AND the speed of structure generation — fewer means faster.
A total row budget plus a department cap; distribution follows compliance risk intensity — hotspots get more rows.
Focused / Balanced / Broad control materiality — both how critical the model's suggestions are and the volume level per department.
Master data fields carry confirm/unlock; freely entered custom values are adopted verbatim.
AI suggests risk types, suppliers, processes, risks (including KRIs) and tasks in the context of industry, country, regulator and framework(s).
Per-department calls run behind a blocking progress modal with live findings; canceling offers "keep partial result vs. discard."
Materiality-dependent volume caps per department keep calls compact (~20–30s) and parsable; a 60s timeout per call prevents one stuck department from blocking the whole run.
Recovers even truncated or malformed AI responses (multiple retries) and works offline with a static fallback.
Generation only fires on a truly empty, never-saved list — never on imported data or existing versions.
Tasks are generated per risk, deduplicated by name, and their risk links are merged.
Processes are matched to the right supplier via keyword overlap.
Claude for public regulatory content; an EU/private model for personal KYC/monitoring data.
Uploaded document → AI suggests additional risks and tasks, the user selects which to keep.
Rename, delete, reorder, add your own entries, upload your own lists, compare against AI suggestions, accept or reject.
A hierarchical structure; sub-processes override the parent process's values for scoring.
A risk with short name, type, likelihood/impact and key risk indicators.
Mitigating tasks with status, note, evidence and a many-to-many link to risks.
Maintainable lists; suppliers carry service descriptions that feed process matching.
A complete structure can be generated for a department added after the fact.
Cascading cleanup of orphaned links with clear confirmation dialogs.
createdAt/modifiedAt on the project and every row, stamped centrally and content-aware.
Likelihood × impact with scale-relative bands (Low/Medium/High/Critical).
Inherent × (1 − mitigation), derived from the weighted completion level of the linked tasks.
Same formula, but only AI-accepted or auditor-confirmed evidence reduces the risk.
Fixed per project; bands and normalizations scale automatically with N².
Calculated per department from staff, IT systems, suppliers, complexity and automation.
Weighted scoring per supplier based on the processes they run, banded relative to the maximum.
Upload (png/jpg/webp/pdf/txt/md/csv/doc/docx), write a statement, or submit — deliberately without AI in this dialog.
Returns accepted / rejected / inconclusive plus a rationale and a PII flag, including a placeholder guard and a "to accept" checklist.
AI creates an audit-ready Word template per task (including evidence to attach), versioned under "Evidence templates."
File bytes are never persisted; when personal data is detected, only the review verdict is retained.
Confirm (even without a file) or decline with a mandatory due date; overdue declined tasks are flagged.
none / accepted (AI) / rejected (AI) / inconclusive / confirmed (auditor) / declined (auditor).
A single POST /api/v1/events endpoint — one-way (systems → Goveron), idempotent, with a bearer key per source system.
Stable slugs survive every risk regeneration and are mapped to real risk IDs.
Events raise KRIs, create and trigger case tasks, and feed auto-evidence into the post-audit score.
Kept separate from the AI's suspicion — with fields suspicious, reason, at and confirmed_by.
A monitoring case flagged "suspicious," plus a KYC block (block_user/oasis/oasis_24h, 72h SLA breach).
Pseudonymous IDs, masked labels and a secure deep link back into the source system.
KRIs per risk with a value and a target, defined only where clearly meaningful (budget ≈ 10 per company, max. 2 per risk).
Exceeding or falling below the target triggers an alert and highlights the affected indicator.
External KYC/monitoring events raise critical risk indicators and feed through to risks, tasks and reports.
All risk KRIs collected with value/target as a central early-warning overview.
A KRI can be bound to a data source and recalculated automatically with every new data delivery.
The frameworks determine which commercial indicators are material — they appear even before any BWA, in a "waiting for BWA" state.
Deterministic detection of the reporting-month column via the annual overview, prior-year comparison and ZM counterparties for concentration risk.
Gross margin, personnel cost ratio, operating result margin, total cost ratio, revenue YoY, material cost ratio and receivables concentration risk.
A floor (≥) or ceiling (≤) per indicator with clear breach detection.
A single chart-of-accounts mapping serves all projects; the monthly BWAs and calculated values live on the project.
Existing risk KRIs are bound to a BWA metric and recalculated on every upload — the BWA doesn't create new KRIs, it feeds them.
Every monthly BWA is stored as a document version (category "Financial reports (BWA)") — re-uploading a period appends a new version.
Metrics on departments, processes, risks, tasks, completion, evidence, risk reduction, distributions, supplier ranking, KRIs, heatmaps, CRIs and framework readiness.
One flat row per risk × mitigating task, filterable and exportable as CSV.
A single department or an overall view with metrics, processes, risks and tasks.
A 7-column graph — departments → processes → risk types → risks → tasks → policies → suppliers — with hover tracing.
A risk heatmap plus complexity, automation and dependency metrics.
A dedicated view for running through stress scenarios.
Every dashboard formula is documented directly inside the app.
The control structure is determined via chunked discovery, never hardcoded (e.g. all 93 ISO 27001 controls).
With a fixed standard, every control is shown as covered/gap by matching task-control references.
Without a fixed catalog = the share of risks with at least one live mitigating control.
AI drafts a mitigating control for each uncovered control or risk, mapped and merged in.
A catalog must be fully covered — row costs against budget are flagged before drafting begins.
A precise control ID or paragraph is only cited when certain, otherwise left blank.
An expandable table with a detail drawer: purpose, controls governed, regulatory references, template section.
AI drafts a sample policy matching scope + framework, versioned under "Policy templates," returned as a download and as evidence.
Every entry keeps an ordered version history; an upload adds a version, it never overwrites.
Owner/department: upload + download (no delete); admin: delete; auditor: read-only.
GDPR-consistent: file bytes are never persisted; after a reload the metadata remains, the bytes are gone.
How well the home-market infrastructure fits a target country + regulator + framework(s) — explicitly flagged as a rough estimate.
A heuristic base match; AI refinement is only accepted if it covers at least half of the departments.
Additional staff/IT systems/suppliers per department, an overall grade (Strong → Minimal) and CSV export.
A JSON file; import accepts either a whole project or a single version file.
Curated customer work is protected from AI overwrites through snapshots.
Every save writes a version with editor, time, audit flag, data and three scores; older versions are read-only.
When an auditor opens a project, the system freezes any drifted lists as a baseline version.
After finalization, AI suggestions must be manually approved.
The first process save locks master data for non-admins; risk names lock after their first save.
Runs the full guided wizard for their own project.
Restricted to their own department, can edit but not delete, Essentials view, same day-to-day navigation.
Read-only except for evidence, lands on the tasks, freezes an audit baseline on opening.
Full access via the admin console, including all projects.
Switchable live; all global styles rebuild instantly.
AI-generated content can be produced in the local language, while the interface stays in English.
Edit locally up to the first save; after that, every change persists immediately.
Structured guidance for every page, including admin tabs, with a clear "not legal advice" notice.
Every destructive action runs through a single, consistent dialog that lists the resulting cascades.
Background fetch with a skeleton state, "use your own value," a cancel row, and a timeout fallback to static lists.
Cycle through status, relevance, complexity and automation with a click.
A switchable level of detail — day-to-day work vs. full control.