Built with FlutterFlow
Volkano AI - Enterprise Ad Intelligence Platform
Gokul Shivappa 🏭🚀
Volkano.ai - Enterprise Ad Intelligence Platform
Client testimonial highlighting the seamless user experience
Project Overview
Volkano AI is a sophisticated B2B SaaS platform that revolutionizes competitive advertising analysis for marketing teams and agencies. Built entirely in FlutterFlow, this enterprise-grade application transforms how businesses understand market dynamics by providing AI-powered insights into competitor ad strategies across Meta's Ad Library.
App Snapshots
Technical Architecture & Innovation
The platform represents a complex technical achievement, featuring a robust architecture that seamlessly integrates multiple technologies:
Frontend: Built in FlutterFlow following atomic design principles, with 48 custom functions, 20 custom widgets, and 68 custom actions
Backend Infrastructure: Firebase for authentication and real-time updates, Supabase for structured data storage
AI Engine: Gemini AI integration for analyzing ad creatives across 50+ dimensions
Local Storage: Hive NoSQL database for efficient client-side data management
Payment Processing: Custom-modified Chargebee integration
Visualization: Syncfusion charts enhanced with custom widgets
Key Challenges & Solutions Delivered
1. Browser Memory Limitations with Massive Datasets
Challenge: The platform needed to handle thousands of ad creatives with images, videos, and extensive metadata, which exceeded browser memory limits when using traditional state management.
Solution: Implemented an innovative storage architecture using Hive's IndexedDB wrapper. Created a partitioned storage system where ads are indexed and stored in chunks, with an LRU (Least Recently Used) cache system. The custom widgets dynamically calculate browser memory capacity and load/unload data accordingly, ensuring smooth performance even with 1000s ads.
2. Real-Time Data Processing Performance
Challenge: Processing and analyzing competitor data across 50+ dimensions while maintaining responsive UI performance.
Solution: Developed a sophisticated
parseData function that intelligently prioritizes data processing based on the user's current view. When a user navigates to a specific section (e.g., "Video Duration Analysis"), that section's data is processed first while other sections process in parallel background threads. This approach reduced perceived loading time by 80%.3. Complex Data Visualization Requirements
Challenge: Displaying multi-dimensional competitive insights through interactive charts while maintaining performance.
Solution: Created custom visualization widgets, including:
Horizontal bar charts with real-time tooltips and hover effects
Semi-donut charts for demographic breakdowns
Duration distribution graphs with period comparisons
Custom loading states with shimmer effects
Each widget implements efficient animation controllers and responsive design breakpoints for optimal display across devices.
4. Payment Integration Edge Cases
Challenge: The existing Chargebee Flutter package lacked proper state management for payment completion, browser refresh scenarios, and cancellation handling.
Solution: Forked the original package and implemented custom modifications to handle:
Payment success/failure state persistence
Browser refresh/cancelling during the payment flow
Proper callback handling for all edge cases
Session management across payment redirects
Core Features Developed
Competitor Research Module
7 comprehensive sub-modules: Overview, Ads, Videos, Hooks, Images, Ad Copy, and Creative Audit
Granular analysis: Each ad creative analyzed across 50+ dimensions including market sophistication, themes, demographics, and performance metrics
Natural language search: AI-powered search allowing queries like "show me all ads using green screen"
Advanced Filtering & Search System
Multi-dimensional filtering across creative formats, themes, duration, demographics, and more
Real-time filter updates with optimized performance
Saved filter combinations for recurring analysis
Team Collaboration Features
Multi-workspace architecture supporting agencies with multiple clients
Role-based access control (Owner, Admin, Member, Guest)
Real-time collaboration with instant updates across team members
Workspace-specific competitor tracking and analysis
Intelligent Data Management
Automatic data caching with expiration handling
An efficient snackbar notification system for user feedback
Progressive data loading with visual indicators
Memory-aware infinite scrolling for large datasets
Business Impact
The platform enables marketing teams to:
Reduce campaign research time from hours to minutes through automated analysis
Identify winning creative patterns across competitors instantly
Make data-driven decisions backed by AI-powered insights
Scale competitive analysis across multiple brands and markets efficiently
Technical Innovations
Hybrid Storage Architecture: Combined Supabase for persistent storage with Hive for local caching, creating a responsive experience even with massive datasets
Intelligent State Management: Custom state synchronization system that prevents race conditions and ensures data consistency across complex UI updates
Component Reusability: Atomic design implementation resulting in 70% code reuse across the application, significantly improving maintainability
Performance Optimization: Custom scroll virtualization and lazy loading reduced initial load time by 60% while maintaining smooth 60fps scrolling with thousands of items
Development Approach
The project followed enterprise-grade development practices:
Structured data types for type safety and maintainability
Comprehensive error handling and edge case management
Responsive design supporting desktop and tablet devices
Custom preloader for enhanced perceived performance
Extensive use of Flutter's async patterns for non-blocking operations
Live Application
This platform demonstrates the capability to build production-ready enterprise applications in FlutterFlow while solving complex technical challenges through innovative architecture and custom development.
Like this project
Posted Jun 3, 2025
Developed a competitor research and ad analytics SaaS platform for Volkano.ai using FlutterFlow.
Likes
9
Views
104
Timeline
Mar 12, 2025 - May 28, 2025
