Not all OCR is the same. Understand the difference between template-based and AI-powered extraction, then test with your actual documents—free.
Drag and drop files, connect a cloud drive, or set up email auto-forwarding. Any file format works—PDF, JPEG, PNG, TIFF, or digital documents.
The AI identifies fields by context and meaning, not fixed coordinates. Names, dates, amounts, and custom fields are extracted automatically.
Get structured output in Excel, Google Sheets, CSV, or JSON. Use the REST API for direct integration into your systems.
“We tested four OCR tools before finding one that didn’t require a template for every document layout. This was the only platform that handled all our document types out of the box.”
“We evaluated tools based on accuracy across 12 different document formats. The AI approach consistently beat template tools because it didn’t break when vendors changed their layouts.”
“The free trial let us test with our actual documents before committing. We uploaded 50 pages across five formats and got accurate results on every one. That was the proof we needed.”
Audited controls over a sustained period, not a point-in-time check.
Bank-grade encryption at rest and TLS 1.2+ in transit.
Documents deleted within 24 hours. No copies retained.
AI OCR tools fall into two broad categories: template-based systems that require you to define extraction zones for each document layout, and AI-powered systems that use vision models to read documents contextually without pre-configuration. Template tools work well when you process a small number of fixed document formats, but they become a maintenance burden as document variety increases. AI-powered tools handle any layout on the first upload, making them the better choice for teams that process documents from many different sources.
The most common mistake teams make when evaluating OCR tools is testing with a single, clean document format. Real-world performance depends on how the tool handles variety: different layouts, mixed quality scans, multi-page documents, and edge cases like handwritten annotations or stamps overlapping text. An effective evaluation should include at least 10 different document formats representative of your actual workload, including your worst-quality inputs.
Beyond extraction accuracy, the downstream integration matters. An OCR tool that produces perfect results but requires manual export and reformatting for your ERP still creates a bottleneck. Look for tools that offer multiple output formats (Excel, CSV, JSON), API access for programmatic integration, and email auto-forwarding for hands-free intake. Lido provides all of these along with custom AI columns that let you define extraction rules beyond standard fields.
Security is a non-negotiable criterion for any tool processing business documents. At minimum, require SOC 2 Type 2 certification, AES-256 encryption, and a clear data retention policy. For healthcare or financial services, confirm HIPAA compliance and the availability of a BAA. Any AI OCR tool worth considering should make its security posture transparent before you upload a single document.
Template-based OCR requires you to define extraction zones for each document layout. When a document format changes or a new layout appears, a new template must be created. AI-powered OCR uses vision models that understand document context and layout semantically, extracting fields by meaning rather than position. This means AI OCR handles new document formats on the first upload without any configuration.
Key evaluation criteria include accuracy on varied document layouts, support for your specific document types, output format flexibility (Excel, CSV, JSON, API), integration options with downstream systems, security certifications like SOC 2, pricing model, and whether the tool requires template setup or training data. Test with your actual documents rather than vendor-provided samples.
AI OCR tools can automate 90 to 98 percent of data entry work depending on document quality and complexity. Most teams keep a human review step for fields where the AI confidence score falls below a set threshold. The goal is reducing manual effort from hours to minutes by only reviewing flagged exceptions.
Modern AI OCR tools include preprocessing that corrects skew, adjusts contrast, and denoises images before extraction. AI models trained on degraded documents perform significantly better than traditional OCR on low-quality inputs. Severely damaged or illegible documents will still produce low confidence scores, which trigger manual review.
Enterprise-grade AI OCR tools offer SOC 2 Type 2 compliance, AES-256 encryption at rest, TLS 1.2+ in transit, and automatic document deletion after processing. Some also offer HIPAA compliance with BAA agreements for healthcare documents. Lido meets all of these standards and deletes uploaded documents within 24 hours of processing.
Start free with 50 pages. Upgrade when you’re ready.
Built on Lido’s OCR engine
Built on Lido’s OCR engine
Built on Lido’s OCR engine