Custom AI agent · Documents & Data
AI OCR Quality Review Agent
Catch extraction errors before they become bad business data.
Review OCR output against document evidence, flag uncertainty, and route low-confidence fields for correction.
- Higher confidence in extracted document fields
- Fewer downstream corrections caused by scan or layout errors
- Clearer human review queues for ambiguous documents
Starting at $300 USD/month
Starting price is $300 USD/month for a tailored solution. Your final proposal defines the scope, deliverables and payment terms. Additional integrations, usage, hosting and ongoing support are scoped and priced before work begins.
What is an AI OCR quality review agent?
An AI OCR quality review agent helps teams validate the fields extracted from scanned documents before those fields enter a business workflow. It compares the OCR result with the visible document structure, checks required fields and confidence signals, identifies likely character, layout, table, or alignment errors, and prepares a focused review task. Tranki configures the agent around your document types, field rules, confidence thresholds, redaction requirements, and correction workflow. It does not silently rewrite uncertain information or treat a low-quality scan as reliable evidence.
What it can handle
Field-level quality checks
Review required fields, dates, identifiers, totals, tables, checkboxes, and repeated values against the permitted source document and extraction result.
Layout and reading-order review
Detect likely column shifts, merged lines, missing sections, rotated pages, handwriting limitations, and other layout conditions that can affect extracted data.
Confidence and anomaly flags
Highlight low-confidence characters, inconsistent values, unexpected formats, missing fields, and mismatches that deserve a human check.
Correction-ready review tasks
Create a concise issue list with the affected page or field, evidence context, suggested correction path, and reason for escalation without overwriting the source.
Where it can help
Invoices and purchase records
Check extracted supplier, date, line-item, tax, and total fields before they reach accounts payable or procurement workflows.
Forms and applications
Validate required fields, identifiers, selections, and page structure before a form is routed for eligibility, service, or case processing.
Contracts and operational records
Flag uncertain clauses, dates, references, tables, and signatures for a reviewer before structured data is used for reporting or action.
How it works
A step-by-step workflow your team can review before launch.
1. Define document quality rules
Tranki maps supported document types, required fields, acceptable formats, confidence thresholds, redaction rules, and the human owner for each exception.
2. Compare extraction to source
The agent reviews the permitted document and OCR output, preserves the original, and checks field-level and layout-level signals.
3. Flag and explain issues
It separates likely extraction errors from unreadable or missing evidence, records the reason, and avoids guessing a corrected value when the source is unclear.
4. Route for correction
A focused review task goes to the appropriate operator or system. Approved corrections are recorded through your existing process, with the original evidence retained.
Built around your business
What we configure
- Document types, page layouts, field dictionaries, required values, table rules, confidence thresholds, and acceptable formats
- Redaction, retention, reviewer roles, correction forms, exception categories, and multilingual or handwriting handling policies
- Connections to approved OCR, document, workflow, ERP, CRM, case, or data-quality systems with least-privilege access
What we need from you
- Representative scans and the current OCR output for clear, difficult, rotated, tabular, and incomplete documents
- A definition of required fields, acceptable formats, review thresholds, and the system of record for corrections
- Data permissions and retention rules for documents, extracted fields, personal information, and review evidence
Clear boundaries before launch
What it will not do
The agent does not invent text, infer missing facts, certify a document, make an eligibility or financial decision, expose sensitive document content, or overwrite original evidence without an approved action. Unreadable scans, signatures, handwriting, identity documents, legal records, and high-impact fields require the defined human review.
How success is measured
Track field-level agreement, review catch rate, false-flag rate, correction turnaround, repeat error types, document failure rate, extraction completeness, reviewer workload, and downstream rework caused by OCR quality issues.
Frequently asked questions
What does an AI OCR quality review agent do?
It checks extracted fields and document structure against approved source evidence, flags uncertainty or mismatches, and routes focused correction tasks to a human or workflow.
Does it replace OCR?
No. It reviews OCR output and the conditions that affect its reliability. The OCR engine, document source, and final correction process remain part of your configured workflow.
Can it correct extracted values automatically?
It can suggest a correction when the source is clear and your workflow permits it, but uncertain or high-impact fields should be reviewed and approved by a person.
Which documents can it review?
The workflow can be tailored to invoices, forms, applications, contracts, records, and other document types with defined layouts, fields, and quality rules.
Can it review tables and multi-page documents?
Yes, when the document type, table rules, page relationships, and available extraction context are defined. It can flag reading-order, alignment, and missing-section issues.
How does it handle unreadable scans or handwriting?
It marks the evidence as unreadable or uncertain and routes it for the required human review rather than guessing what the source says.
What is included in the $300/month starting price?
The $300 USD/month starting price covers a scoped, tailored solution. The final proposal defines the review workflow, integrations, usage, support, deliverables, and payment terms.
