Volkano AI - Enterprise Ad Intelligence Platform

Alfadesmeta

Completed work

Flutter Developer

Flutterflow Developer

AI Developer

Cloud Firestore

Firebase

Supabase

Advertising

Volkano.ai - Enterprise Ad Intelligence Platform

App Snapshots

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.

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

🔗 volkano.web.app

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