v-modal/vmodal_sdk_flutter

What it solves

VModal for Flutter provides a way for mobile developers to integrate multimodal video and image search into Android and iOS apps. It eliminates the need for developers to manage complex machine learning pipelines, vector databases, or raw AI infrastructure, allowing users to find specific moments in videos using natural language, speech, or imagery.

How it works

The SDK acts as a gateway to V-Modal's backend AI services. It allows developers to organize media into projects, collections, and streams. Videos are uploaded as streams to avoid memory overhead, and the backend processes them into searchable mathematical representations (vector indexing). Users can then perform semantic searches using text prompts, and the SDK returns structured data containing relevance scores and timestamps to jump directly to specific video frames.

Who it’s for

Mobile developers building Flutter applications for iOS and Android who want to add deep visual intelligence, such as semantic video search, automated tagging, or visual discovery features to their media-heavy apps.

Highlights

• Multimodal Search: Search across video, speech, text (OCR), and imagery using natural language.
• Streamed Uploads: Handles large video files via streamed, signed uploads with live progress tracking and cancellation support.
• Mobile-Optimized: Designed for mobile lifecycles, supporting credential rotation and deterministic resource closing.
• Typed API: Provides a small, typed Dart API for managing collections and performing searches without imposing a specific UI.
• Cross-Platform: Native Dart implementation ensuring consistent behavior across Android and iOS.