Use case
IDs and proof-of-address to verified JSON in one call
Passports, ID cards and utility bills become schema-valid JSON — every value with confidence, page and bbox evidence.
The problem
Onboarding queues grow with every campaign, and every applicant brings a different combination of documents.
- 01Document variety. Passports, national IDs, driving licences and bills arrive as PDFs, scans and phone photos in several scripts.
- 02Manual retyping. Analysts copy names, dates and addresses by hand. Backlogs stretch onboarding from minutes to days.
- 03Unreadable edge cases. Glare, skew and low-resolution photos defeat template OCR — files bounce back to the applicant.
- 04Audit exposure. A verified name with no source trail fails the first regulatory sample. Dumps carry no evidence.
The solution
Fieldry extracts your KYC schema from any file and returns cited values — plus validation and forensics.
- 01Any ID layout. No per-country templates. The schema defines the output; the interpreter reads whatever layout arrives.
- 02Null-honest fields. Missing expiry or unreadable number returns null with status missing — never a guessed value.
- 03Validation on top. Checksum and format rules catch bad document numbers before they enter the customer record.
- 04Evidence attached. Each value ships with confidence, page and bounding box. Review is a click, not a reopen.
Extraction checks
Search the KYC checks.
See what each check returns.
Every check Fieldry runs on an onboarding pack — search and inspect what each returns.
Any ID layout
No per-country templates. The schema defines the output; the interpreter reads whatever layout arrives.
Null-honest fields
Missing expiry or unreadable number returns null with status missing — never a guessed value.
Validation on top
Checksum and format rules catch bad document numbers before they enter the customer record.
Command preview
Cited identity values
Names, dates and document numbers mapped to your schema with confidence and source box on each.
Anatomy of a KYC file
It starts with an upload: an ID photo taken at an angle and a utility bill PDF. Both land in one onboarding pack, each with its own layout, language and quality.
Fieldry splits, classifies and extracts both against your KYC schema — validated, forensics-screened and evidenced — and the reviewer sees cited values instead of scans.
- InputID photo + utility bill PDF
- OutputSchema-valid JSON with evidence
- ReviewOnly flagged fields need eyes
From upload to verified record
Reviewer clears flagged fields from evidence and approves — the file is audit-ready.
AnalystValidation and forensics run: expiry checked, tamper signals screened, missing stays null.
FieldryFiles split and classified, fields extracted to schema with confidence and evidence.
FieldryApplicant uploads an ID photo and a bill; layouts, scripts and quality differ.
Document
4 milestones, newest first.
Key benefits
Onboarding that moves at applicant speed and holds up at audit.
Minutes, not days
Straight-through parsing clears clean files instantly; analysts handle exceptions only.
No templates
New ID layout from a new market parses on day one against the same schema.
Multilingual
Latin and Cyrillic scripts handled by the interpreter — no dictionary maintenance.
File-grade proof
Every approved value traces to its source line for regulators and QA alike.
Verify your next applicant today
Run a real ID + bill pack on free credits and trace any value back to its source.
Get startedRelated products
Related use cases
Related industries
Passports, national ID cards, driving licences and residence permits — including phone photos. Low-confidence fields route to review instead of guessing.
They return null with status missing. Set per-field review thresholds; nothing is ever invented.
EU hosting is available, a DPA ships from day one, and sensitive workloads can move to the self-host path.
Yes — REST API with sync ?wait for instant decisions, webhooks for async, and SDKs for Python/JS stacks.
Parse your first document today
One API for extraction, evidence and automation.