Less manual keying
Reduce repetitive data entry so teams spend their time on exceptions and decisions instead of retyping documents.
AI Data Extraction
Read invoices, contracts, forms and scans automatically, validate every field against your business rules, and send clean structured data straight into your systems.
- UnderstandComplex documents
- ValidateBusiness rules
- ConnectYour systems
Extracted fields · Samplelive
- SupplierReading…
- Invoice no.Queued
- Due dateQueued
- TotalQueued
Low-confidence fields go to a reviewer
Outcomes
Illustrative aims for document-heavy workflows. Results vary by document quality, variety, volume, validation rules and integrations.
Faster document turnaround
Move invoices, forms and records from inbox to system without waiting for a queue of manual handling.
Cleaner downstream data
Validated, consistently structured fields reduce rework in ERP, CRM, finance and reporting systems.
Traceable to the source
Every extracted value links back to where it was found on the original document for quick verification.
Understand complex documents
Read layouts, tables, stamps, handwriting and multi-page files, then classify each document and locate the fields that matter.
Apply business rules
Validate values against your formats, reference data, cross-field checks and approval thresholds before anything is saved.
Connect business systems
Deliver clean, structured output into your ERP, CRM, databases, workflows and APIs without extra manual steps.
Overview
AI data extraction automatically reads documents such as invoices, contracts, forms, emails and scans, finds the fields and values that matter, validates them against your rules and delivers them as structured data. Unlike template-based OCR, it adapts to layout variation and keeps people in the loop wherever confidence is low.
Book a free consultation callCompare
See how an intelligent, rule-aware extraction pipeline compares with keying data by hand or relying on fixed-template OCR.
Evaluation areaAarvexa AI Data ExtractionManual data entryTemplate-based OCR
Services
End-to-end document automation, from capture and understanding to validation, review, integration and ongoing improvement.
Document Intake and Capture
Ingest PDFs, scans, photos, emails and attachments from inboxes, portals, SFTP folders and APIs, then clean, de-skew and classify them for extraction.
Custom Extraction Models
Combine OCR, layout understanding and language models trained or prompted around your document types, fields and schemas.
Validation and Business Rules
Check formats, totals, dates, reference data and cross-field logic so only trustworthy values move forward.
Confidence Scoring and Human Review
Score every field and route uncertain values to a simple review screen, with the source highlighted for fast verification.
System Integration
Deliver structured output to ERP, CRM, accounting, databases, data warehouses and workflows through APIs, webhooks or files.
Monitoring and Continuous Improvement
Track accuracy, exceptions and throughput, and feed reviewer corrections back so extraction improves with real usage.
The Problem
Document-heavy processes create a hidden tax on speed, accuracy and morale, and it grows with every new supplier, form and channel.
Repetitive keying
Skilled people spend hours retyping values from documents into systems instead of analysing, deciding or serving customers.
Inconsistent formats
Every supplier, partner and customer sends documents differently, so fixed templates and simple rules keep breaking.
Slow downstream processes
Approvals, payments, claims and onboarding wait until someone has finished reading and entering the data.
Hidden rework
Typos, missed fields and mismatched totals surface late, creating corrections, disputes and reconciliation effort.
Accuracy
Accuracy comes from layered controls, not a single model. We test against representative documents and keep measuring in production. We do not promise error-free output.
Field-level confidence
Each extracted value carries its own confidence, so automation and review decisions are made field by field, not document by document.
Cross-field validation
Totals, dates, tax values and identifiers are checked against each other to catch errors a single read would miss.
Reference-data matching
Suppliers, products, accounts and codes are matched to your master data so values land in the right place.
Human-in-the-loop review
Low-confidence and rule-breaking items go to reviewers with the source highlighted, keeping accountability with your team.
Feedback learning loop
Reviewer corrections are captured and used to refine models, prompts and rules as your documents evolve.
Our Approach
A structured process validates documents, rules, integrations and accuracy before broader deployment.
Discovery and document audit
We review your document types, volumes, channels, systems, pain points and success measures to choose the right first workflow.
Sample set and schema design
Representative documents are collected and the fields, formats and validation rules are defined with your subject experts.
Model build and rules
Extraction models, prompts, validation logic and review screens are built and tuned on your sample documents.
Pilot with real documents
The pipeline runs on live documents alongside your current process, with measured results and agreed acceptance criteria.
Deploy, monitor and improve
Validated workflows roll out with dashboards, alerts and feedback loops, then expand to new document types.
Document Types
AI data extraction works across the document types that slow down finance, operations, legal, insurance and logistics teams.
Invoices and Receipts
Capture supplier, invoice number, dates, line items, taxes and totals, then match them to purchase orders and post to finance.
Contracts and Agreements
Pull parties, effective dates, renewal terms, payment terms and key clauses into a searchable, structured record.
Claims and Application Forms
Read checkboxes, names, policy numbers and amounts from forms and attachments to speed up intake and triage.
Shipping and Trade Documents
Extract bill of lading numbers, parties, goods, weights and codes from logistics and customs paperwork.
Emails and Attachments
Monitor inboxes, classify messages and attachments, and extract the requests, orders and details inside them.
Scanned and Handwritten Records
Digitize legacy archives, handwritten notes and low-quality scans into searchable, structured data with review for uncertain text.
Technology
Flexible OCR, language models, orchestration, storage and integrations combined around your documents and systems.
Tesseract
PaddleOCR
Google Document AI
AWS Textract
Azure AI Document Intelligence
LayoutLM
Document Reading and Layout
OCR and layout models chosen for your document types, languages, scan quality and hosting requirements.
Product names are listed as examples of tools we work with. Third-party trademarks belong to their owners.
Trust
Documents often hold your most sensitive information. Controls are scoped around your data, deployment model and policies.
Data privacy by design
Encryption, masking, tenant isolation and secure processing help protect sensitive documents and the data extracted from them.
Role-based access
Reviewers and systems only see the documents, fields and queues their role allows.
Sensitive-field redaction
Personal, financial and confidential fields can be masked or excluded before storage, review or model processing.
Data-training controls
Private endpoints, no-training settings and client-approved model providers reduce unauthorized reuse of your documents for training.
Audit trails
Source, extracted value, rule results, reviewer changes and approvals remain traceable through configurable logs.
Regulatory alignment
Architectures can support applicable privacy laws, retention policies and your organization's governance requirements.
We support your security and compliance teams with controls and documentation. We do not certify outcomes, and fit depends on your data, jurisdictions and policies.
Why Aarvexa
16+ years of engineering, 1,000+ projects delivered and a 98% successful go-live rate, with accuracy-first design and transparent staged implementation.
Built around your documents
Every pipeline is designed for your document types, fields, rules, systems and review process, not a generic template.
Deep engineering background
Aarvexa delivers enterprise AI engineering and integration rather than reselling a standardized extraction product.
Agentic and AI expertise
Our teams combine OCR, vision, language models and agent workflows to handle messy, real-world documents.
Privacy-first architecture
Access control, redaction, auditability and human review are designed in from the start, not added afterwards.
Native system integration
Extracted data lands directly in your ERP, CRM and databases instead of another disconnected tool.
Transparent, staged delivery
Discovery, pilot on real documents, measurable acceptance criteria and phased rollout reduce risk before scale.
Explore Broader AI Capabilities
Go beyond extraction with AI agents
Once your documents become structured data, AI agents can act on it by approving, routing, reconciling and responding. Explore Aarvexa's AI agent development services for automating complex workflows across your organization.
Explore AI Agent DevelopmentInvoice Processing Automation
Illustrative scenarioSample view
Manual keyingReduced
Invoice turnaroundFaster
Exceptions routedAutomated
Invoice Processing Automation
From inbox invoices to validated finance data
A finance team receives invoices in dozens of layouts through email, portals and scans, and keys each one into the ERP by hand. Aarvexa can design an extraction workflow that reads every invoice, validates it against your rules and master data, and sends only uncertain fields to a reviewer.
- Captured invoices from email, portals and scans into one intake pipeline.
- Extracted supplier, dates, line items, taxes and totals with per-field confidence.
- Validated totals and matched suppliers and purchase orders against master data.
- Routed low-confidence fields to a reviewer screen with the source highlighted.
- Posted approved data to the finance system with a full audit trail.
Illustrative scenario. Details are representative, not client-specific, and outcomes vary by document quality, supplier variety, volume, rules and integrations.
Discuss a similar projectFAQ
Straight answers on AI data extraction, accuracy and validation, security and data handling, integration, pricing and who we are.
AI data extraction automatically reads documents such as invoices, contracts, forms, emails and scans, finds the fields that matter, validates them and delivers structured data to your systems. People review only the values the system is unsure about.
Invoices, receipts, contracts, claims and application forms, shipping and trade documents, emails with attachments, and scanned or handwritten records. We confirm fit after reviewing sample documents.
Traditional OCR turns an image into text and often relies on fixed templates. AI extraction understands layout and context, adapts to new formats, validates values against your rules and scores confidence for each field.
Start with one high-volume, well-defined document type, such as supplier invoices, where success measures are clear. A short consultation and a sample-document review help choose the best first workflow.
No. The goal is to handle layout variation, scans and photos. Quality still affects results, so we assess your documents early and design review steps for hard cases.