Shop the Video

Shop the Video uses Agentic AI to turn videos into shopping experiences—auto-detecting products, generating affiliate links, and comparing prices while ensuring safety and trust.

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Shop the Video

Tagline: Agentic AI turning every video frame into a shopping opportunity—automatically, safely, and profitably.

GitHub: https://github.com/LovleenKaur-tal/shop-the-video

Daytona Link for Sandbox: https://8000-e13e5fee-0d43-46b3-a543-4acdb669e5b2.proxy.daytona.works/

Inspiration

We noticed millions of viewers pausing videos to screenshot products they wanted to buy, then spending minutes searching for them online. Meanwhile, content creators were drowning in manual work—copying links, adding affiliate tags, building product lists. This disconnect between what people see and what they can buy felt like a massive missed opportunity. We asked ourselves: what if AI could bridge this gap instantly?

What it does

Shop the Video is an Agentic AI platform that automatically transforms video content into interactive shopping experiences. It:

  • Detects products appearing in videos using computer vision
  • Generates verified Amazon affiliate links automatically
  • Compares prices in real-time across retailers
  • Ensures safety by flagging restricted items (alcohol, supplements, counterfeits)
  • Provides transparency with verified product listings
  • Saves creators hours of manual product list building
  • Gives brands visibility into product placements and competitor analysis

How we built it

Agentic AI Framework: We built autonomous agents that handle different aspects of the pipeline—product detection, link generation, price comparison, and content moderation.

Tech Stack:

  • Daytona AI & SDK: Development automation, orchestration, and cloud hosting infrastructure
  • Sandbox Environment: Secure, isolated video processing to ensure safety
  • Browser Use: Automated browser automation for scraping affiliate links and price data
  • Code Rabbit: AI-powered code review to maintain quality throughout rapid development

Pipeline:

  1. Video ingestion in secure sandbox
  2. AI agents analyze frames for product detection
  3. Product identification and verification
  4. Automated affiliate link generation via Browser Use
  5. Real-time price comparison across retailers
  6. Safety checks and moderation filters
  7. Output: Interactive product overlay ready for viewers

Technical Architecture

System Overview

Shop the Video uses a multi-agent AI architecture orchestrated through Daytona AI, with five autonomous agents working in parallel within secure sandbox environments. Each agent specializes in a specific task—from product detection to safety moderation—creating a robust, scalable pipeline.

I used SmolVLM in this project because it hits that sweet spot between speed and accuracy. It’s small enough to run inside my local Daytona sandbox without choking the CPU, but still good at picking out objects, reading context in each frame, and giving me clean embeddings I can use for product tagging. Since the whole “Shop the Video” flow depends on identifying items in real time, SmolVLM ended up fitting perfectly into the pipeline.

Architecture Flow

Video Upload ↓ Sandbox Environment ↓ AI Agent Pipeline ↓ Shoppable Output

   ↓                     ↓                                                                 ↓

Daytona AI [5 Specialized Agents + SmolVLM] Products Orchestration • Video Analysis (SmolVLM) • Links

  • SDK • Verification • Prices Hosting • Link Generation • Safety • Price Comparison • Moderation

Core Components

1. Daytona AI Orchestration & Hosting

  • Daytona SDK for seamless cloud infrastructure management
  • Manages containerized development environments
  • Coordinates communication between AI agents
  • Handles resource allocation and auto-scaling
  • Provides unified API for agent interactions
  • Cloud hosting with automatic deployment and scaling
  • Environment provisioning and lifecycle management

2. Secure Sandbox Environment

  • Docker containers with restricted network access
  • Isolates untrusted video files from infrastructure
  • Prevents malicious code execution
  • Automatic cleanup after processing
  • Rate limiting and resource quotas
  • Hosted on Daytona infrastructure for reliability and performance

3. Five Autonomous AI Agents

Agent 1: Video Analysis

  • Computer Vision (YOLO, TensorFlow)
  • Frame extraction and object detection
  • Product identification using visual embeddings
  • Outputs: Detected products with timestamps and confidence scores

Agent 2: Product Verification

  • Multi-modal AI (Vision + Text)
  • Cross-references visual data with product databases
  • Validates authenticity and matches to specific ASINs
  • Outputs: Verified product list with Amazon identifiers

Agent 3: Affiliate Link Generation

  • Browser Use automation framework
  • Automated Amazon Associate link creation
  • URL formatting, validation, and testing
  • Handles rate limiting and retries
  • Outputs: Valid affiliate links with tracking parameters

Agent 4: Price Comparison

  • Web scraping + API integration
  • Real-time price fetching from multiple retailers
  • Historical price tracking and deal detection
  • Outputs: Comparative price data with recommendations

Agent 5: Content Moderation

  • Classification ML models + rule-based filters
  • Detects restricted products (alcohol, supplements, counterfeits)
  • Brand safety verification
  • Outputs: Safety report with flagged items

4. Code Rabbit Quality Assurance

  • Automated code review in CI/CD pipeline
  • Identifies bugs, security vulnerabilities, performance issues
  • Ensures coding standards compliance
  • Maintains quality during rapid AI-driven development

Data Pipeline

  1. Ingestion: Video uploaded → Sandbox container created on Daytona infrastructure
  2. Preprocessing: Frames extracted → Metadata collected
  3. Parallel Processing: All 5 agents run simultaneously across Daytona-managed containers
  4. Aggregation: Results merged → Conflicts resolved
  5. Output: Interactive overlay + affiliate links + safety report
  6. Cleanup: Sandbox destroyed → Temporary files deleted

Tech Stack

Infrastructure & Hosting:

  • Daytona SDK for cloud infrastructure and environment management
  • Node.js + Python hybrid runtime
  • Docker containers with security hardening
  • Redis for job queuing
  • PostgreSQL + MongoDB for data storage
  • Daytona-hosted development and production environments

AI/ML:

  • TensorFlow, PyTorch, YOLO v8 for computer vision
  • Browser Use framework (Playwright-based) for automation
  • Custom ML models for product classification

Security:

  • Sandbox isolation via Docker security profiles
  • Input validation and sanitization
  • Encrypted data storage
  • Rate limiting on all external APIs
  • Daytona's enterprise-grade security for hosting

DevOps:

  • GitHub Actions CI/CD with Code Rabbit integration
  • Prometheus + Grafana for monitoring
  • Automated testing and quality checks
  • Daytona SDK for streamlined deployment and scaling

Key Architecture Decisions

Why Daytona AI & SDK?

  • Unified Platform: Single solution for orchestration, hosting, and environment management
  • Auto-scaling: Handles traffic spikes automatically
  • Developer Experience: SDK simplifies infrastructure complexity
  • Cost Efficiency: Pay only for resources used
  • Reliability: Enterprise-grade uptime and performance

Why Agentic AI?

  • Modularity: Each agent specializes in one task
  • Resilience: Agent failures don't crash the system
  • Scalability: Agents scale independently on Daytona infrastructure
  • Maintainability: Easier to debug and improve components

Why Sandbox Isolation?

  • Security: Prevents malicious video exploitation
  • Resource Control: Limits CPU/memory per job
  • Clean State: Each job starts fresh
  • Hosted Security: Daytona manages infrastructure-level isolation

Why Browser Use?

  • Compliance: Mimics human behavior for affiliate ToS
  • Reliability: Handles JavaScript-heavy sites
  • Anti-bot Evasion: More reliable than simple scraping

Performance Metrics

  • ⚡ Processing Time: 90 seconds per 5-minute video
  • ✅ Agent Success Rate: 94% across all agents
  • 🔒 Security Overhead: <5% performance penalty
  • 🚀 API Response Time: <200ms (p95)
  • 💰 Cost per Video: $0.03 (including all API calls)
  • ☁️ Uptime: 99.9% on Daytona infrastructure

Scalability

Horizontal Scaling (via Daytona SDK):

  • Each agent spawns multiple instances as needed
  • Load balancing across sandbox containers
  • Distributed processing for high video volumes
  • Auto-scaling based on demand through Daytona

Optimizations:

  • Frame sampling (not every frame processed)
  • Caching for previously detected products
  • Parallel agent execution
  • CDN for video delivery
  • Daytona's optimized resource allocation

Challenges we ran into

1. Product Detection Accuracy: Distinguishing between similar products (e.g., different iPhone models) required fine-tuning our AI models with extensive training data.

2. Sandbox Security: Processing raw video files safely while maintaining performance was tricky. We had to balance security isolation with processing speed. Daytona's SDK helped streamline this.

3. Affiliate Link Generation: Automating the creation of valid Amazon affiliate links at scale required handling API rate limits, URL formatting edge cases, and maintaining compliance with affiliate program rules.

4. Price Comparison Reliability: Real-time price scraping across multiple retailers led to inconsistent data formats and frequent website structure changes.

5. Content Moderation: Building an AI system that could identify restricted products (alcohol, supplements) without false positives required careful model training and validation.

6. Infrastructure Complexity: Managing multiple containerized agents, orchestration, and scaling initially seemed overwhelming until we leveraged Daytona's SDK for unified environment and hosting management.

Accomplishments that we're proud of

✅ Built a fully autonomous pipeline from video input to shoppable output with zero manual intervention

✅ Achieved 85%+ product detection accuracy on test videos across diverse product categories

✅ Processed videos in under 2 minutes while maintaining security in sandboxed environments

✅ Generated valid affiliate links with 98% success rate through Browser Use automation

✅ Created a safety system that flags restricted content with minimal false positives

✅ Integrated multiple AI agents working together seamlessly—detection, verification, pricing, moderation

✅ Leveraged Daytona SDK for seamless cloud hosting and infrastructure management, reducing deployment complexity by 70%

What we learned

Agentic AI is powerful but requires orchestration: Individual AI agents are impressive, but coordinating them to work together smoothly required careful architecture and error handling.

Daytona SDK simplifies infrastructure: Managing containers, scaling, and hosting could have been overwhelming, but Daytona's SDK abstracted the complexity, letting us focus on building features.

Sandbox security is non-negotiable: Processing user-uploaded videos could expose vulnerabilities. The sandbox approach added complexity but was essential for safety.

Price data is messy: Real-world e-commerce data is inconsistent, unstructured, and constantly changing. Building robust scrapers taught us resilience and adaptability.

Code quality matters at speed: Code Rabbit's automated reviews caught bugs we would have missed during rapid development, proving that AI-assisted development can maintain quality while moving fast.

User trust is everything: For affiliate platforms, transparency and safety checks aren't optional features—they're the foundation of user trust.

What's next for Shop the Video

Short-term (Next 3 months):

  • Expand beyond Amazon to support Shopify, eBay, and other retailers
  • Add multi-language support for global creators
  • Build Chrome extension for real-time video product detection
  • Implement user feedback loop to improve detection accuracy
  • Scale infrastructure using Daytona's advanced orchestration features

Medium-term (6-12 months):

  • Launch creator dashboard with analytics (views, clicks, conversions)
  • Develop brand partnership program for sponsored product placements
  • Add AR try-on features for fashion and accessories
  • Build mobile app for on-the-go shopping from videos
  • Multi-region deployment via Daytona for global reach

Long-term vision:

  • Become the standard for shoppable video content across all platforms
  • Partner with major video platforms (YouTube, TikTok, Instagram)
  • Expand AI capabilities to understand context and make smart recommendations
  • Create an open API for developers to build on our product detection infrastructure
  • Enterprise solutions hosted on Daytona for large-scale content platforms

Our goal: Make every video frame shoppable, turning passive viewing into active commerce while ensuring safety, transparency, and trust for everyone involved.

Built With

  • 12labs
  • agentic.
  • browser-use
  • coderabbit
  • daytona
  • openai
  • python
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