Stop reading docs. Start making decisions.

Luxembourg locked its register behind legitimate-interest checks. Cayman, Angola, BVI, opaque by design. Even where data exists, access runs out, and the case goes back to manual.

The trust deed sat in a shared inbox. The customer questionnaire response is buried in a thread. The case is open because nobody’s had time to read a PDF.

Directors, shareholdings, registered addresses. Transcribed by hand, one line at a time. Mistakes creep in. And the real work, the judgment, hasn’t started yet.

The document lives in four places. Nobody has both sides open at once, so nobody actually compares. The field says whatever the last person typed.

Ownership moves. Directors change. Registries update when they update. Your team keeps going back out to confirm what’s current, then entering it by hand, because the filing hasn’t caught up yet.

Remediation means working through five, seven, ten thousand entities, the same compare-and-update exercise, one at a time. Today it lives in spreadsheets thrown between systems, with no way to scale beyond more people and a longer week.

PDF, CSV, JSON, and plain text — what your clients actually send. Trust deeds, articles of association, incorporation certificates, registry extracts, questionnaire responses, structure charts, annual reports, ownership registers. If it’s computer-readable, Strise parses it.

Multilingual by default. The extraction model reads the document in its native language and maps every field to the working language in your Strise instance. A Luxembourg trust deed in French, an Estonian registry extract, a German questionnaire response, the entity data lands in the same structured fields either way.

Every extracted value is grounded in the source: the field, the page, the exact text it came from. Low-confidence extractions are surfaced for review, not auto-applied. And nothing, high-confidence or low, is written to the entity without an analyst’s click. Accuracy isn’t trusted; it’s verified, row by row.

Documents stay isolated to your Strise instance. Nothing is shared across customers. Nothing trains a shared model. Your enriched data sharpens your own intelligence layer, not anyone else’s. GDPR-compliant by default, with DPAs and data-processing documentation available at any point during evaluation.

Every AI step is labelled and logged. Extraction is proposed, not committed, the analyst accepts, overrides, or edits before anything touches the entity. Every automated decision maps to a human review. When an examiner asks what the model did and what the human decided, the audit trail answers both.

It triggers a monitoring alert. Nothing silently overwrites an analyst decision. The registry update and the original document-sourced edit sit side-by-side in the same compare view your team used to create the record. You reconcile the conflict once, and the audit trail keeps both versions.