AI OCR for gas station operations
- 20K+
- transactions processed in a single day
Intelligent Document Processing Services
Intelligent Document Processing (IDP)
Every business runs on documents. Invoices, contracts, applications, reports, forms, claims. Most of these are still processed manually, someone reads the document, enters the data, routes it for approval.
We build intelligent document processing systems that extract, classify, validate, and route document data automatically. Not just OCR that reads text. Systems that understand what the document means and what needs to happen next.
Extraction from PDFs, scanned documents, images, and mixed formats
Classification, validation, and workflow routing built in
95%+ accuracy on structured document types with exception handling for the rest
Proven: gas station OCR system that processed 20,000+ transactions in a single day
Recent outcomes
Voice AI · Research
6× deeper insights
Text-based interviews converted to automated phone calls
AI Automation · Ops
20k+ txns day one
Manual invoice OCR across 40+ gas stations
Loyalty · Retail
1,062 users in 4 weeks
SuperValu & Centra loyalty platform with receipt validation
SaaS · Logistics
2,000+ shipments yr 1
Multi-carrier shipping hub for Indonesian eCommerce
4.9
on ClutchThe problem
Sound familiar?
Team spending hours manually entering data from invoices, forms, or applications?
Document errors causing downstream problems in your ERP, CRM, or compliance system?
Short answer
RaftLabs builds intelligent document processing systems for clients across the US, UK, Europe, and Canada. Our gas station OCR system processed 20,000+ transactions in a single day during real-world testing. IDP extracts, classifies, validates, and routes document data automatically, beyond what basic OCR does. A focused single-document-type system runs $30,000 to $70,000.
Key takeaways
- RaftLabs builds IDP systems for clients across the US, UK, Europe, and Canada
- Our gas station OCR system processed 20,000+ transactions in a single day during real-world testing, with no manual data entry
- Structured document extraction delivers 95%+ field accuracy with exception handling for the rest
- Single-document-type IDP systems cost $30,000 to $70,000; multi-document-type platforms run $70,000 to $180,000
- Systems include classification, validation, and workflow routing to downstream ERP or CRM
Trusted by
Proof
- 100+
- software products shipped since 2015
- RaftLabs delivery record
- 4.9/5
- average client rating across delivered projects
- Clutch, verified reviews
- Fixed price
- scope and cost agreed in writing before any development starts
- Every RaftLabs engagement
Manual document entry gets more expensive as you grow
Hiring more people to process more documents is not a growth strategy. The cost compounds with every new vendor, every new form type, every new market.
According to McKinsey's research on the future of work, 60% of employees could save at least 30% of their time by automating repetitive manual tasks. For document-heavy operations, the bulk of that time sits in data entry, classification, and routing, work that IDP handles automatically.
Intelligent document processing replaces the data entry work, and the errors that come with it. The human role shifts from entering data to reviewing exceptions: the edge cases the system flags because it is not confident. The ratio improves over time as the system sees more documents.
OCR reads text. IDP understands the document.
Most teams already have some OCR in place. The gap is everything that happens after the text comes off the page: knowing what the document is, pulling the right fields, checking them, and getting them into a system of record. That is the line between OCR and intelligent document processing.
| Basic OCR | Intelligent document processing | |
|---|---|---|
| What it does | Converts an image of text into machine-readable characters | Reads, classifies, extracts named fields, validates, then routes |
| Document type | You tell it what it is looking at | Classifies invoices, contracts, and claims automatically |
| Field extraction | A template per layout, rebuilt when the layout changes | Models that hold up across vendors and layout variation |
| Validation | None: raw text out | Business rules, master-data lookup, cross-field checks |
| Low-confidence data | Silent errors passed downstream | A confidence score routes edge cases to a review queue |
| Output | A block of text | Structured data posted to your ERP, CRM, or database |
Capabilities
What we build
- 01Invoice and AP automation
Automated extraction of vendor details, line items, totals, payment terms, and PO references from supplier invoices in any format: digital PDF, scanned paper, photographed receipt, EDI, or e-invoice XML. Extracted data is validated against ERP master data with two-way and three-way matching before payment approval, approval routing follows your thresholds from auto-approval to director sign-off, and approved invoices post automatically to your ERP or accounting platform.
- Built with
- SAP · Oracle · NetSuite · Dynamics 365 · QuickBooks · Xero
- 02Contract data extraction
Extraction of key contract terms from supplier agreements, customer contracts, NDAs, and service agreements: parties, dates, notice periods, auto-renewal clauses, payment terms, liability caps, and governing law. Each clause carries a confidence score so ambiguous drafting is flagged for legal review rather than silently extracted with a wrong value, and structured data flows to your contract database with alerts 90, 60, and 30 days before renewal.
- Built with
- Ironclad · Juro · Conga
- 03Claims and application processing
Document classification and data extraction for high-volume intake workflows where a single submission spans multiple document types. Insurance claims get form extraction, supporting document classification, and cross-document consistency checks with an automatic request-for-information email when documents are missing, and loan applications get income validation against bank statement deposits and automated credit bureau lookups. Documents from one submission are linked and presented as a unified record.
- 04Receipt and expense capture
OCR extraction from retail, fuel, toll, and restaurant receipts submitted as photos, scans, or email attachments. Image pre-processing corrects rotated, angled, and faded thermal receipts before extraction of merchant, date, line items, tax, and totals, and expense policy validation checks each receipt against your rules and cites the specific rule violated. Our gas station OCR system processed 20,000+ transactions in a single day during testing.
- Built with
- Concur · Expensify · Image pre-processing
- 05Medical and clinical document processing
Structured data extraction from medical records, discharge summaries, lab reports, referral letters, and prior authorisation forms, reducing the manual abstraction work clinical coders and case managers perform. Clinical NLP extracts diagnoses, medications, and procedures with ICD-10 code suggestions presented alongside supporting evidence, HIPAA compliance is architectural with documents staying in your cloud VPC, and extracted data delivers to EHRs via FHIR.
- Built with
- Clinical NLP · ICD-10 · Epic and Cerner via FHIR
- 06Customs and logistics documents
Automated processing of the international trade document set: bills of lading, commercial invoices, packing lists, certificates of origin, and customs entries. Documents are classified by type so each routes to the right extraction model. Extracted HS codes are validated against the current tariff schedule, with likely misclassifications flagged for broker review. Validated data pre-populates customs entry forms and feeds your logistics platforms.
- Built with
- HS-code validation · CBP 7501 and UK CDS · SAP TM · Oracle TMS
Show us your document problem.
Send us a sample of the document type, the data you need extracted, and where it needs to go. We'll give you an accuracy estimate and a fixed-cost proposal.
How IDP projects run
Why us
Why teams choose RaftLabs
- 01Senior engineers build what they scope
The engineers who assess your document processing problem also build the solution. No bait-and-switch, no offshore handoff after the contract is signed. The team you meet in week 1 ships in week 12.
- 02Fixed price before development starts
We scope the work, calculate the cost, and lock it in writing before any development starts. A scope change is a change request: priced, agreed, or dropped. It never absorbs into the project and appears on the final invoice.
- 03Shipping production software since 2015
Clients include Vodafone, T-Mobile, Aldi, Nike, Cisco, and Lockheed Martin. Track record across AI, automation, SaaS, and enterprise platforms spanning healthcare, fintech, logistics, and insurance.
- 04Compliance built in from the start
GDPR, HIPAA, SOC 2 compliance requirements are scoped in week 1, not retrofitted before launch. We have shipped HIPAA-compliant document processing systems for US healthcare clients and GDPR-compliant IDP platforms for European markets.
What clients say
What our clients say
Three-year average engagement. Founders and operators describing the work in their own words. No marketing varnish.
Charles E.
USAEntrepreneur at Aggie Technologies
All of the sprints were completed on schedule and on budget. We highly recommend RaftLabs!
Stay on topic
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Read moreFrequently asked questions
Intelligent document processing (IDP) is the automated extraction, classification, and routing of data from business documents. It goes beyond basic OCR (which converts images to text) by understanding document structure, extracting specific fields (invoice number, vendor name, amount, date), validating extracted data against business rules, and routing the output to downstream systems. A complete IDP system handles the full document lifecycle, intake, classification, extraction, validation, exception handling, and delivery to ERP, CRM, or workflow systems.
Structured documents (fixed-position fields): invoices, receipts, purchase orders, application forms, tax documents. Semi-structured documents (variable layout, consistent fields): contracts, lease agreements, insurance claims, medical records, bank statements. Unstructured documents: free-form correspondence, email bodies, handwritten notes (lower accuracy, higher manual review rate). Accuracy is highest on structured and semi-structured documents from a consistent set of vendors or form types. We assess document type distribution and accuracy expectations during scoping.
Extraction accuracy depends on document quality and structure. Typed, well-formatted PDFs from a known set of vendors typically achieve 95-99% field extraction accuracy. Scanned documents with variable quality achieve 85-95%. Mixed handwritten content achieves 70-85%, with higher exception rates routed for human review. We provide accuracy benchmarks on a sample of your actual documents before committing to a production build, not industry averages that may not apply to your document set.
Every extraction carries a confidence score. Fields below a defined threshold are flagged for human review rather than passed to downstream systems. The exception queue shows the document, the extracted value, and the confidence level, a reviewer confirms or corrects in seconds rather than processing from scratch. Most mature IDP systems achieve 85-95% straight-through processing; the remaining 5-15% get human review. This is configurable, you set the confidence threshold based on error tolerance and review capacity.
Document output integrates via REST API, direct database write, or file-based export depending on your existing system's capabilities. We integrate with ERPs (SAP, Oracle, NetSuite), accounting platforms (QuickBooks, Xero), contract management systems, claims platforms, and custom databases. For systems without API access, file-based export (structured CSV, JSON, or XML) writes to a shared location your system polls. Integration architecture is scoped before build.
A focused IDP system for a single document type with extraction, validation, exception queue, and ERP integration typically runs $30,000 to $70,000. Multi-document-type platforms with classification, multiple extraction models, workflow routing, and multiple system integrations run $70,000 to $180,000. Monthly operating costs after launch are low. The main ongoing cost is cloud OCR and AI API calls, which scale with document volume.
Work with us
Tell us what you need. We'll tell you what it would take.
We scope Intelligent Document Processing Services in 30 minutes. You walk away with a clear cost, timeline, and approach. No commitment required.
- Scope and cost agreed before work starts. No surprises. No obligation.
- Working prototype within 3 weeks of kickoff.
- Pay by milestone. You see progress before each invoice.
- 60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
- All conversations are NDA-protected.