Multicloud AI & ERP / Cloud AI: Machine Learning & Generative AI
Why it matters
Manual data entry from documents is slow, costly and error-prone. Automating extraction speeds up finance, claims, onboarding and compliance, provided low-confidence results still get a human check.
How it works
From page to system of record
A document or image is read by OCR and layout analysis that understands text, tables and checkboxes. Field extraction pulls out values such as invoice numbers and totals into a schema. A confidence check routes uncertain fields to a person, and clean data flows into the ERP, CRM or data lake.
AWS, Azure and Google Cloud compared
| AWS | Azure | Google Cloud | |
|---|---|---|---|
| Document extraction | Amazon Textract | Azure Document Intelligence | Document AI |
| Multimodal extraction | Bedrock Data Automation, Nova 2 Omni | Content Understanding | Gemini multimodal |
| Image analysis | Amazon Rekognition | Azure AI Vision | Vision AI |
| Custom extractors | Blueprints | Custom models | Custom Extractor |
| Human review | Augmented AI (A2I) | Review workflows | Human review in Document AI |
What makes each cloud different
AWS
Textract handles forms, tables and queries, and Bedrock Data Automation turns documents, images, audio and video into structured JSON using blueprints. Augmented AI adds human review for low-confidence results.
Azure
Document Intelligence offers prebuilt models for invoices, receipts and IDs plus custom models, and Content Understanding extracts to schemas from mixed media.
Google Cloud
Document AI provides OCR, form and layout parsers, and its Custom Extractor uses generative AI to learn new document types from only a few samples. Gemini reads PDFs and images natively.
Design decisions that matter
- 01Extract to a fixed schema
Downstream systems need consistent fields.
- 02Confidence thresholds per field
Automate the sure, review the unsure.
- 03Prebuilt models first
Custom only for unusual documents.
- 04Measure straight-through rate
The share processed with no human touch.
Common mistakes we see
- Full automation from day one. Errors flow into financial systems.
- Ignoring layout. Tables and multi-column pages scramble.
- No feedback loop. Reviewer corrections should improve the models.
A practical 30-day plan
- Week 1
Pick one document type and define the target fields.
- Week 2
Test prebuilt extraction on real samples.
- Week 3
Add confidence routing and human review.
- Week 4
Connect to the system of record and track straight-through rate.
How NTS helps
NTS automates document processing on AWS, Azure and Google Cloud, covering invoices, claims, contracts and onboarding documents, with human review built in and integration into your business systems.
What you get
- Automated extraction from invoices, forms and contracts
- Human review for low-confidence results
- Integration with your business systems
- Accuracy tracking by document type
Typical outcomes
- Hours of manual data entry removed
- Faster processing of documents
- Higher accuracy with less effort
How we work with you
- 1Assess
A focused review of your document AI across AWS, Azure and Google Cloud. We look for the gaps we find most often: full automation from day one, ignoring layout and no feedback loop.
- 2Design
A target architecture and roadmap built on the decisions that matter most: extract to a fixed schema, confidence thresholds per field, prebuilt models first and measure straight-through rate.
- 3Build
Hands-on delivery alongside your team. We pick one document type and define the target fields, test prebuilt extraction on real samples, add confidence routing and human review, and finally connect to the system of record and track straight-through rate.
- 4Run and improve
We monitor accuracy, add new document types and retrain extraction as formats change.
Why teams choose NTS for document AI
- Real-world documents
We handle messy scans, tables and handwriting, not just clean samples.
- Humans in the loop
Review steps keep accuracy high where it matters.
- End-to-end automation
Extracted data flows straight into your systems.
Book a free 30-minute review
Talk to an NTS architect about your document AI on AWS, Azure and Google Cloud.