Nanonets vs Klippa: Multi-Account Detection Comparison
When bank statements contain multiple accounts (checking, savings, credit card) in a single PDF, both Nanonets and Klippa struggle with automatic detection and separation. Compare their template-based approaches to Zera Books' AI-powered multi-account detection.
What Multi-Account Detection Actually Means
Multi-account detection refers to a tool's ability to identify and separate multiple financial accounts within a single PDF document. This is common in banking where clients receive consolidated statements showing:
Primary business account with daily transactions, deposits, withdrawals
Interest-bearing account with monthly transfers, interest accrual
Business credit card purchases, payments, fees
For accounting firms managing multiple clients, receiving these consolidated statements is routine. Each account needs to be:
- Identified: Which account type is this? What's the account number?
- Separated: Transactions must be split into individual files for import
- Categorized: Each account has different chart of account mappings
- Reconciled: Imported to the correct QuickBooks/Xero account
The Manual Alternative
Without automatic multi-account detection, bookkeepers must:
- 1. Manually identify where each account starts and ends in the PDF
- 2. Copy transactions for each account into separate spreadsheets
- 3. Label each file with account type and number
- 4. Format each file for QuickBooks/Xero import
- 5. Repeat for every client, every month
This process takes 5-10 minutes per statement. For firms with 50+ clients, that's 4-8 hours monthly.
Nanonets Multi-Account Limitations
Template-Based Approach
Nanonets uses machine learning models that require template training for each document format. For multi-account statements, this creates significant operational overhead:
You must create and train individual templates for checking accounts, savings accounts, and credit cards. Each template needs 20-30 sample documents and manual field labeling.
When a single PDF contains multiple accounts, Nanonets doesn't automatically separate them. You either process the entire PDF as one document (mixing all transactions) or manually split the PDF before upload.
When banks change statement formats (which happens frequently), all affected templates must be retrained. For firms processing statements from dozens of banks, this becomes a continuous maintenance burden.
You need to build custom logic (via API integration) to route each page to the correct template. This requires identifying account types programmatically—essentially solving the detection problem yourself.
Real Workflow Impact
An accounting firm with 50 clients using Nanonets for multi-account statements:
- Initial setup: 10-15 hours creating and training templates for each bank/account type combination
- Monthly processing: 3-5 minutes per statement manually splitting PDFs or routing to templates
- Ongoing maintenance: 2-4 hours monthly retraining templates when banks update formats
Klippa Multi-Account Limitations
API-First, Configuration-Heavy
Klippa is designed as an API service for developers to integrate OCR capabilities into custom applications. For multi-account bank statements, this creates significant technical barriers:
Klippa's bank statement parser focuses on extracting data from single-account statements. There's no built-in functionality to detect or separate multiple accounts within one PDF. The API returns a flat array of transactions without account-level segmentation.
To handle multi-account PDFs, you need to build custom post-processing logic that analyzes transaction patterns, account numbers, and section breaks to separate accounts. This requires development resources most accounting firms don't have.
While Klippa offers pre-built parsers for major banks, these still require configuration for optimal accuracy. Multi-account statements from regional banks or credit unions often need custom template setup, adding operational complexity.
Klippa is API-only with no built-in dashboard for uploading statements, viewing results, or managing conversions. You must build your own interface or use command-line tools, making it inaccessible for non-technical bookkeepers.
Cost Structure
Klippa charges per API call (per page processed). For multi-account statements:
- • 10-page statement = 10 API calls
- • Must process entire PDF even if you only need one account
- • Volume discounts require annual contracts
- • Development costs for custom integration
Implementation Timeline
Setting up Klippa for multi-account processing:
- • API integration: 20-40 hours development
- • Custom account separation logic: 15-30 hours
- • Testing across bank formats: 10-20 hours
- • Total: 6-12 weeks to production-ready
Zera Books Multi-Account Detection
AI-Powered Automatic Separation
Zera AI is trained on 3.2+ million financial documents and dynamically identifies account boundaries within consolidated statements. Upload a multi-account PDF and receive separate Excel files for each account—zero configuration required.
Zera AI identifies checking, savings, credit card, loan, and investment accounts by analyzing transaction patterns, account numbers, interest calculations, and statement structure. No manual labeling or template training.
Each detected account is exported to its own Excel file with proper metadata (account number, type, statement period, opening/closing balances). Files are named automatically:ClientName_Checking_XXXXXX.xlsx
Each account's transactions are automatically categorized for your chart of accounts. Checking account deposits go to "Income", credit card purchases to "Expense" categories, with 95%+ accuracy based on transaction descriptions.
Zera AI adapts to new bank formats automatically. When Chase updates their statement layout, your workflow doesn't change. The AI re-learns format variations continuously from real-world documents without requiring manual retraining.
The Complete Workflow
Drag and drop a consolidated statement containing checking, savings, and credit card accounts.
AI identifies account boundaries, transaction blocks, and account metadata automatically (30-60 seconds).
Receive 3 separate Excel files (one per account) with transactions categorized and formatted for QuickBooks/Xero import.
One-click import to the correct QuickBooks/Xero accounts. Duplicate detection prevents double-entries.
Time saved: 5-10 minutes per statement (no manual splitting, no template configuration, no post-processing)
Processing Time Comparison
Time required to process a 15-page consolidated statement with checking, savings, and credit card accounts
| Workflow Step | Nanonets | Klippa | Zera Books |
|---|---|---|---|
| Initial Setup (one-time) | 10-15 hours (template training) | 40-80 hours (custom dev) | 0 minutes (ready immediately) |
| Upload & Route to Templates | 2-3 min (manual routing) | 3-5 min (API config) | 30 sec (single upload) |
| Processing Time | 1-2 min | 1-2 min | 30-60 sec |
| Account Separation | 5-8 min (manual splitting) | 8-12 min (custom scripting) | Automatic (included in processing) |
| Transaction Categorization | Not included (manual or custom) | Not included (manual or custom) | Automatic (AI categorization) |
| Format for Import | 3-5 min (CSV formatting) | 3-5 min (CSV formatting) | Pre-formatted (QBO/CSV ready) |
| Total Time Per Statement | 11-18 min | 15-24 min | 1-2 min |
Real CPA Experience with Multi-Account Statements
How an accounting professional handles messy consolidated PDFs from dozens of clients
"My clients send me all kinds of messy PDFs from different banks. This tool handles them all and saves me probably 10 hours a week."
The Challenge
Ashish manages bookkeeping for 60+ small business clients across different industries. Most clients use multiple bank accounts (operating checking, payroll account, savings, business credit cards) and send consolidated statements as single PDFs.
The Solution
With Zera Books' multi-account detection, Ashish uploads each client's consolidated statement and receives separate, categorized files for each account. No manual splitting, no template configuration, no custom development.
The Impact
10 hours saved weekly that previously went to manually separating accounts and formatting data. Month-end close now happens 2 days faster, and clients receive updated financials mid-month instead of at month-end.
When Each Tool Makes Sense
Consider Nanonets If...
- You process single-account statements from a very limited set of banks (2-3 formats)
- You have development resources to build custom account separation logic via their API
- You need OCR for other document types (invoices, receipts, IDs) beyond bank statements
- You're comfortable managing template maintenance as banks update statement formats
Note: For most accounting firms managing multi-account statements from diverse banks, the setup and maintenance overhead outweighs the benefits.
Consider Klippa If...
- You're building a custom fintech application that needs OCR as one component
- You have in-house developers to integrate the API and build post-processing logic
- You process single-account statements and don't need account separation
- You need specialized OCR for European bank formats (Klippa's strength)
Note: Klippa is designed for developers, not end-user bookkeepers. Implementation requires significant technical expertise and ongoing maintenance.
Choose Zera Books If...
- You regularly receive multi-account statements from diverse banks and credit unions
- You need automatic account detection and separation without manual configuration
- You want AI-powered transaction categorization ready for QuickBooks/Xero import
- You need to start processing statements immediately without technical setup
- You value predictable unlimited pricing over per-page fees
- You want a complete workflow platform (client management, batch processing, conversion history)
Best for: Accounting firms, bookkeeping practices, CPAs managing 10+ clients with diverse banking relationships
The Fundamental Difference
Nanonets and Klippa are general-purpose OCR platforms that happen to process bank statements. They require custom configuration, template training, or development work to handle multi-account scenarios—because multi-account detection wasn't their core design goal.
Zera Books is purpose-built for accounting professionals processing bank statements at scale. Multi-account detection, automatic categorization, and QuickBooks/Xero integration are built into the core product, not afterthoughts requiring customization.
Ready to Stop Manually Splitting Bank Statements?
Upload multi-account PDFs and receive separate, categorized Excel files for each account. No templates, no configuration, no development required. Start processing in 60 seconds.
Try for one weekProcess unlimited statements • Automatic multi-account detection • AI categorization included