Client Background
Finovora is an EU-based expense management platform serving small and mid-sized businesses that operate across European jurisdictions. The platform specializes in processing multilingual invoices that often contain local tax identifiers, regional formatting, and VAT compliance fields. Finovora's core value proposition is to streamline financial documentation workflows while maintaining strict adherence to EU tax regulations.
To meet client expectations and regulatory standards, Finovora required an automated pipeline that could parse and classify expense records without human involvement—while also integrating directly into a Bubble.io frontend built for both authenticated users and guests.
The Problem
Finovora's operations were hampered by:
Manual Invoice Processing: Staff had to handle thousands of image-based and PDF invoices monthly.
Regional Format Complexity: Documents contained mixed-language content, currency symbols (EUR, GBP), and country-specific VAT formats.
Table Structure Variability: Tables embedded within invoices varied in structure and were difficult to parse using traditional tools.
No Backend Infrastructure: The platform relied entirely on Bubble.io and could not accommodate server-side processing.
Limitations mentioned caused delays, human error, and compliance risks—particularly when capturing regulatory identifiers like VAT IDs or categorizing expenses across multiple departments.
Our Solution
To automate invoice intake and classification, NextGen deployed a frontend-only architecture that leveraged Nanonets, OpenAI GPT-4, and native Bubble.io plugins.
Intelligent OCR & Data Structuring with Nanonets
Custom Model Training: Built a Nanonets model specifically trained on EU invoice layouts, enabling accurate detection of totals, line items, VAT IDs, and localized currencies.
API Connector Integration: Configured Bubble API Connector to transmit uploaded invoices to Nanonets and receive structured JSON responses.
Data Normalization: Applied Toolbox plugin logic to convert currency strings (e.g., “€1.099,00”) into normalized numerical values.
No-Code Workflow Automation in Bubble.io
Frontend Logic-Only Architecture: Built workflows using Bubble.io’s visual logic, bypassing the need for a backend or server.
Visual Repeating Groups: Used Repeating Group elements to render invoice rows dynamically, ensuring compatibility across screen sizes.
Inline Field Editing: Implemented editable text inputs with custom states, enabling users to make live corrections to OCR-extracted data.
Semantic Categorization Using OpenAI GPT-4
Line-Item Classification: Routed structured invoice rows to GPT-4 when Nanonets returned undefined categories.
Accounting-Tuned Prompting: Used a controlled vocabulary aligned to expense taxonomy (e.g., "Legal Services", "Client Entertainment") for more consistent classification.
Batch Parsing: Combined line-item blocks into batch prompts to improve contextual accuracy and reduce API usage.
Access Tier Controls and Filtering Logic
Free-Tier Limiting: Enforced usage caps through Bubble conditional logic, limiting guests to 5 uploads before requiring sign-up.
Filter Components: Built dynamic filters for category and date using Bubble’s front-end state management—enabling real-time toggling without page reloads.
State Persistence: Used session-based memory in Bubble.io to ensure filters and user preferences persisted between uploads.
UX Optimization for Speed and Mobile
Rendering Pipeline: Parsed and rendered uploaded invoices in less than 3 seconds using Bubble-native JSON parsing.
Mobile-Responsive UI: Adjusted all frontend components to scale for tablet and mobile dimensions, improving accessibility and load times.
Results
85% Reduction in Manual Entry: Finovora automated over 85% of its document processing workload.
Zero Backend Infrastructure: The system required no servers, reducing DevOps complexity and hosting costs.
98% Accuracy on VAT and Currency Fields: Custom OCR and classification workflows matched EU documentation standards.
Sub-3 Second Invoice Display: Frontend-only JSON parsing allowed near-instantaneous rendering.
100% Editable UI: Users could override all fields within the dashboard interface.
Persistent Filters: Category and date filters remembered user preferences between sessions.
AI Confidence >98%: GPT-4 fallback classification achieved high semantic accuracy across multilingual invoices.
Minimal API Usage: Batched GPT-4 queries reduced costs while maintaining accuracy.
Why It Matters
The Finovora automation framework demonstrates the power of combining no-code tools with advanced OCR and language models. By embedding automation directly into the Bubble.io frontend, Finovora avoided costly backend deployment and accelerated development timelines. The system's modular design supports other verticals—such as tax filing platforms, procurement software, or HR onboarding portals—seeking automated document parsing with minimal overhead. With robust accuracy, low-latency rendering, and multi-language support, the architecture is well-suited for compliance-heavy industries.
Call to Action
Explore how automation can reshape your document workflows — contact admin@nextgencodingcompany.com or book a call to speak with a technical advisor.
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