From 6 Months to 6 Days: Why Veryfi Outperforms Custom Document AI Builds
Building your own document AI solution sounds appealing. You control the technology, customize features, and avoid vendor dependency. However, recent MIT research reveals a different story: enterprises building their own tools consistently struggle, while purchased solutions deliver more reliable results.
At Veryfi, we’ve been processing documents with AI since before it became the industry buzzword. Today, we help teams go from concept to production in days, not the 6+ months typical for custom builds.
The True Cost of Building In-House
Month 1-2: Finding Specialized Talent
Your first challenge is finding ML engineers who specialize in computer vision for document understanding, multimodal architecture design, and production OCR optimization. This expertise commands $150-250K per engineer. Most teams need at least 3 engineers, bringing Year 1 labor to $600K.
With Veryfi: Sign up at app.veryfi.com, get API keys, and start testing in under an hour.
Month 3-4: Training Data Hell
ML models need thousands of labeled documents. You’ll either spend months manually annotating or pay $50-150K for labeling services. Either way, you’re accumulating costs without processing a single production document.
With Veryfi: Our models are pre-trained on millions of real-world documents. Day 1 Accuracy™ delivers 99.9% extraction immediately.
Month 5-6: When Reality Hits Production
By month six, you might have a working model. It performs well on test data. Then production happens: users submit rotated images, blurry photos, crumpled receipts. Your model struggles with variations you didn’t anticipate.
With Veryfi: We’ve seen these edge cases thousands of times. We handle rotation, quality issues, and format variations automatically.
The Maintenance Trap
Machine learning models drift. Document formats change. Your three-engineer team becomes permanent. That $600K annual cost continues, and grows as you scale.
With Veryfi: We continuously train models across our customer base. Model updates happen automatically without engineering effort on your side.
Compliance Certifications
Processing financial documents requires SOC2 Type 2 (6-12 months, $100-200K), HIPAA (3-6 months, $50-100K), and GDPR compliance (3-6 months, $50-100K). Add $200-400K to Year 1 costs.
With Veryfi: We maintain all certifications. You inherit enterprise-grade security on day one.
Why Generic AI Tools Fail in Production
After ChatGPT’s launch, teams rushed to use generic LLMs for document processing. MIT research revealed: “Generic tools like ChatGPT excel for individuals because of their flexibility, but they stall in enterprise use since they don’t learn from or adapt to workflows.”
The Veryfi Technical Difference
Multimodal Understanding: Generic LLMs are text-only. They don’t “see” spatial relationships or layout hierarchies. Veryfi combines computer vision + NLP to understand both visual layout and semantic meaning.
Intelligent Mobile Capture: Our Veryfi Lens SDK handles capture at the source with edge detection, auto-cropping, blur correction, and fraud detection. By the time images reach our APIs, they’re optimized for maximum accuracy.
Production-Grade Features: We extract line item level data, detect fraud patterns, prevent duplicates, and support custom field extraction. Generic AI just pulls text.
We offer SDKs in 12+ languages with working samples, automated tests, and Postman collections.
Where Document AI Delivers Real ROI
MIT research found that while most AI budgets go to sales and marketing tools, the biggest ROI comes from back-office automation: eliminating BPO services, cutting agency costs, and streamlining operations.
Industry Applications
Accounts Payable: Organizations report 75% reduction in manual labor costs, 90% faster processing, and 95% fewer errors using Veryfi’s APIs.
Expense Management: Combining Lens SDK for mobile capture with our extraction APIs, fintech companies create seamless experiences. Snap a photo, done. Reimbursement in days instead of weeks.
Healthcare: Our HIPAA-compliant processing reduces patient check-in time by 60%, claims errors by 80%, and accelerates reimbursement cycles by 50%.
Property Management: Proptech platforms automate receipt processing, lease management, and vendor invoice validation with 99.9% accuracy.
Construction: Teams streamline invoice processing, PO matching, timesheet digitization, and change order tracking, reducing administrative overhead and improving compliance.
Making the Build vs. Buy Decision
Choose Veryfi When:
✓ Document processing enables your business but isn’t your core product
✓ You need production results this quarter, not next year
✓ You want 99.9% accuracy from day one
✓ You need SOC2, HIPAA, GDPR, CCPA, ITAR certifications ready
✓ You want engineers focused on your actual differentiator
Build In-House Only If:
✓ Document processing IS your core business (you’re selling OCR)
✓ You have truly unique document types no solution handles
✓ You can commit 10+ ML engineers long-term
✓ Your timeline allows 18-24 months before production
The Bottom Line
Research consistently shows purchased solutions deliver more reliable results. We’ve processed millions of documents and solved thousands of edge cases. The competitive advantage isn’t in building OCR, it’s in what you do with the extracted data.
The intelligent document processing market reached $2.30 billion in 2024, growing at 33.1% CAGR through 2030. Organizations report 3x efficiency improvements, 40% productivity gains, and 75% cost reductions after implementing specialized document automation.
We built Veryfi so you don’t have to build document processing yourself. Our multimodal APIs transform documents into structured data with industry-leading accuracy, enterprise-grade security, and fraud prevention, all at lightning speed.
Get Started Today
For Developers: Start your free trial and process your first document in under 60 seconds. No credit card required.
For Decision Makers: Contact our team to discuss your specific use case and ROI projections.
For Product Teams: Explore our API Documentations with interactive examples and code samples in 12+ languages.
At Veryfi, we’ve been processing documents with AI since before it became the industry buzzword. Today, we help teams go from concept to production in days, not the 6+ months typical for custom builds.
The True Cost of Building In-House
Month 1-2: Finding Specialized Talent
Your first challenge is finding ML engineers who specialize in computer vision for document understanding, multimodal architecture design, and production OCR optimization. This expertise commands $150-250K per engineer. Most teams need at least 3 engineers, bringing Year 1 labor to $600K.
With Veryfi: Sign up at hub.veryfi.com, get API keys, and start testing in under an hour.
Month 3-4: Training Data Hell
ML models need thousands of labeled documents. You’ll either spend months manually annotating or pay $50-150K for labeling services. Either way, you’re accumulating costs without processing a single production document.
With Veryfi: Our models are pre-trained on millions of real-world documents. Day 1 Accuracy™ delivers 99.9% extraction immediately.
Month 5-6: When Reality Hits Production
By month six, you might have a working model. It performs well on test data. Then production happens: users submit rotated images, blurry photos, crumpled receipts. Your model struggles with variations you didn’t anticipate.
With Veryfi: We’ve seen these edge cases thousands of times. We handle rotation, quality issues, and format variations automatically.
The Maintenance Trap
Machine learning models drift. Document formats change. Your three-engineer team becomes permanent. That $600K annual cost continues, and grows as you scale.
With Veryfi: We continuously train models across our customer base. Model updates happen automatically without engineering effort on your side.
Compliance Certifications
Processing financial documents requires SOC2 Type 2 (6-12 months, $100-200K), HIPAA (3-6 months, $50-100K), and GDPR compliance (3-6 months, $50-100K). Add $200-400K to Year 1 costs.
With Veryfi: We maintain all certifications. You inherit enterprise-grade security on day one.
Why Generic AI Tools Fail in Production
After ChatGPT’s launch, teams rushed to use generic LLMs for document processing. MIT research revealed: “Generic tools like ChatGPT excel for individuals because of their flexibility, but they stall in enterprise use since they don’t learn from or adapt to workflows.”
The Veryfi Technical Difference
Multimodal Understanding: Generic LLMs are text-only. They don’t “see” spatial relationships or layout hierarchies. Veryfi combines computer vision + NLP to understand both visual layout and semantic meaning.
Intelligent Mobile Capture: Our Veryfi Lens SDK handles capture at the source with edge detection, auto-cropping, blur correction, and fraud detection. By the time images reach our APIs, they’re optimized for maximum accuracy.
Production-Grade Features: We extract line-item level data, detect fraud patterns, prevent duplicates, and support custom field extraction. Generic AI just pulls text.
We offer SDKs in 12+ languages with working samples, automated tests, and Postman collections.
Where Document AI Delivers Real ROI
MIT research found that while most AI budgets go to sales and marketing tools, the biggest ROI comes from back-office automation: eliminating BPO services, cutting agency costs, and streamlining operations.
Industry Applications
Accounts Payable: Organizations report 75% reduction in manual labor costs, 90% faster processing, and 95% fewer errors using Veryfi’s APIs.
Expense Management: Combining Lens SDK for mobile capture with our extraction APIs, fintech companies create seamless experiences. Snap a photo, done. Reimbursement in days instead of weeks.
Healthcare: Our HIPAA-compliant processing reduces patient check-in time by 60%, claims errors by 80%, and accelerates reimbursement cycles by 50%.
Property Management: Proptech platforms automate receipt processing, lease management, and vendor invoice validation with 99.9% accuracy.
Construction: Teams streamline invoice processing, PO matching, timesheet digitization, and change order tracking, reducing administrative overhead and improving compliance.
Making the Build vs. Buy Decision
Choose Veryfi When:
✓ Document processing enables your business but isn’t your core product
✓ You need production results this quarter, not next year
✓ You want 99.9% accuracy from day one
✓ You need SOC2, HIPAA, GDPR, CCPA, ITAR certifications ready
✓ You want engineers focused on your actual differentiator
Build In-House Only If:
✓ Document processing IS your core business (you’re selling OCR)
✓ You have truly unique document types no solution handles
✓ You can commit 10+ ML engineers long-term
✓ Your timeline allows 18-24 months before production
The Bottom Line
| Factor | Build In-House | Veryfi |
| Time to Production | 6-18 months | 6 days |
| Year 1 Cost | $925K+ | $30-110K |
| Maintenance | $600K+/year | Included |
| Compliance | 6-12 months | Day 1 |
| Accuracy | Months to achieve | 99.9% immediately |
Research consistently shows purchased solutions deliver more reliable results. We’ve processed millions of documents and solved thousands of edge cases. The competitive advantage isn’t in building OCR, it’s in what you do with the extracted data.
The intelligent document processing market reached $2.30 billion in 2024, growing at 33.1% CAGR through 2030. Organizations report 3x efficiency improvements, 40% productivity gains, and 75% cost reductions after implementing specialized document automation.
We built Veryfi so you don’t have to build document processing yourself. Our multimodal APIs transform documents into structured data with industry-leading accuracy, enterprise-grade security, and fraud prevention, all at lightning speed.
Get Started Today
For Developers: Start your free trial and process your first document in under 60 seconds. No credit card required.
For Decision Makers: Contact our team to discuss your specific use case and ROI projections.
For Product Teams: Explore our API Documentations with interactive examples and code samples in 12+ languages.