From invoices and receipts to contracts and customer forms, documents power almost every core business process. But manually processing them is time-consuming, error-prone, and resource-intensive. That’s why more businesses are turning to document processing tools powered by AI, OCR, and machine learning to extract data, reduce manual effort, and automate workflows.
But with so many platforms on the market—each claiming to be accurate, scalable, and easy to use—how do you know which one is right for your business?
In this blog, we’ll break down the key features you should look for in a document processing tool, explore why many businesses are considering alternatives to Nanonets, and show how tools like Docsumo are raising the bar for accuracy, speed, and usability.
Why Document Processing Tools Matter More Than Ever
Manual document handling isn’t just inefficient—it’s risky. Data entry errors, delays in processing, and inconsistent formatting can lead to operational bottlenecks and compliance issues. In sectors like finance, logistics, healthcare, and insurance, fast and accurate document processing is critical to daily operations.
Modern document processing tools solve these problems by:
- Extracting structured data from unstructured documents
- Reducing turnaround time for high-volume document workflows
- Enabling real-time decision-making through automation
- Increasing data accuracy and reducing human error
- Freeing up staff from manual, repetitive tasks
With global business processes becoming more digital and data-driven, document processing tools are essential for scalability and efficiency.
1. High-Accuracy OCR and AI Models
At the core of any document processing tool is its OCR (Optical Character Recognition) engine. But OCR alone isn’t enough—modern platforms use AI to understand context, relationships between fields, and document layouts.
What to evaluate:
- Text extraction accuracy, especially in complex documents
- Ability to extract structured data from tables, forms, and multi-page documents
- Recognition of handwritten text and signatures
- Support for low-quality scans and images
- Ability to learn and improve over time through machine learning
Platforms that combine OCR with intelligent parsing and entity recognition provide significantly more value than basic OCR engines.
2. Support for Diverse Document Types
Your platform should be able to handle the document types your business works with daily—and do so without requiring a major setup for each new format.
Common types include:
- Utility bills
- Invoices and receipts
- Identity documents (passports, Aadhaar, driver’s licenses)
- Bank statements and checks
- Tax forms
- Contracts and legal agreements
Many legacy tools struggle with semi-structured or unstructured documents. Choose a platform that adapts to your content, not the other way around.
3. Pre-Built Templates and Quick Start Capabilities
Speed matters. Many businesses exploring alternatives to nanonets are seeking platforms that can deliver results quickly without requiring weeks of onboarding.
Look for tools with:
- Ready-to-use templates for commonly processed documents
- Automatic field detection for structured forms
- A template library that covers finance, logistics, HR, legal, and healthcare sectors
This drastically reduces setup time and accelerates your path to ROI.
4. No-Code Customization and Workflow Flexibility
Every business has unique rules, data fields, and validation logic. Your platform should allow users—especially non-technical teams—to define these without writing code.
Key features:
- Drag-and-drop custom field training
- Field-level confidence scoring and threshold configuration
- Logic builders (e.g., flag if total > approved budget)
- Workflow automation for document routing, approvals, and escalation
Custom workflows are essential for ensuring clean, validated data before it hits your system of record.
5. Human-in-the-Loop Validation
AI isn’t perfect. And when confidence is low, human input is still critical. A good platform will enable seamless manual review with audit-friendly workflows.
Look for:
- Real-time validation queues
- Version history and data traceability
- Role-based access and approval workflows
- Feedback loops that train the model over time
This ensures accuracy without slowing down your document pipeline.
6. API-First Design and Integration Support
A document processing tool should never be a silo. You want it to work with your ERP, CRM, RPA bots, cloud storage, and internal databases.
Ensure the platform offers:
- Robust RESTful APIs with clear documentation
- Webhooks and event triggers
- Integration with tools like Zapier, QuickBooks, Salesforce, SAP, UiPath, and Google Drive
- Flexible export formats (JSON, CSV, XML, XLSX)
An API-first design enables you to build automated, scalable workflows without manual intervention.
7. Scalability and Performance
Processing 100 documents daily isn’t the same as processing 100,000. Your platform should grow with your business.
Evaluate:
- Concurrent document processing capabilities
- Queue handling and latency under high load
- Support for batch uploads and API bulk requests
- Server uptime, SLA guarantees, and load balancing
Platforms that can scale horizontally—especially those built on cloud-native infrastructure—will serve you best in the long term.
8. Security, Compliance, and Privacy Readiness
If your documents contain personal data, financials, or healthcare records, you need enterprise-grade security.
Security features to demand:
- SOC2, GDPR, HIPAA compliance
- AES-256 encryption at rest and TLS in transit
- Role-based access control (RBAC)
- Secure document storage, audit logs, and single sign-on (SSO)
Choose a vendor that takes data governance as seriously as you do.
Why Businesses Are Exploring Alternatives to Nanonets
Nanonets is a popular AI-powered OCR platform, but it’s not without limitations. A growing number of businesses are evaluating alternatives to Nanonets due to the following concerns:
a. Limited Support for Complex or Industry-Specific Documents
Nanonets performs well on standard invoices and receipts, but users have reported challenges with non-standard layouts, tax documents, shipping records, or medical forms.
b. Customization Barriers for Business Users
Building or tweaking custom models often requires technical intervention. Companies with non-technical users may struggle to maintain or update document workflows without engineering support.
c. Pricing and Scalability Concerns
Some users cite challenges in predicting costs at scale, particularly when processing document spikes or using multiple custom models.
These limitations are prompting teams to search for alternatives to Nanonets that offer stronger support for custom workflows, transparent pricing, and pre-trained industry templates.
Conclusion
Selecting the right document processing tool is about more than automating tasks. It’s about improving accuracy, speeding up workflows, and giving your team more control over critical data. As businesses handle increasing volumes of documents, the need for reliable, flexible solutions is only growing.
While Nanonets is a strong option for many use cases, it may not suit every organization. Limitations around complex documents, customization, and pricing have led teams to explore more adaptable alternatives.
Look for tools that offer accurate data extraction, support for diverse document types, easy customization, and strong integration capabilities. Platforms like Docsumo offer a practical, user-friendly approach built to meet both current needs and future growth.