Overview
LTM Decloner.ai and FrameInspect.ai together form an AI/ML powered video intelligence solution that enables end to end content deduplication and quality analysis across large media libraries, spanning macro level title comparison to micro level frame inspection. The solution is purpose built to support enterprises during bulk cloud migration, ongoing catalogue hygiene, storage cost optimization, and legal or compliance driven content governance.
Use cases
Media Analysis and Metadata Management
Decloner.ai and FrameInspect.ai together deliver a comprehensive, AI/ML-powered macro to micro video deduplication and content quality intelligence solution for large media libraries. The solution is designed to support enterprises during: • Bulk cloud migration of media archives • Periodic catalogue hygiene • Cost optimization through storage rationalization • Legal and compliance-driven content management
Details
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Products included
Features and programs
Financing for AWS Marketplace purchases
Pricing
Custom pricing options
Integration guide
Decloner.ai and FrameInspect.ai are tightly integrated with AWS native services to deliver scalable, secure, and high‑performance video intelligence at enterprise scale. The solution is designed to be deployed as a fully managed service, with compute configurations dynamically sized based on the volume of video data to be deduplicated. Depending on workload characteristics, GPU‑enabled compute on Amazon EC2 or containerized workloads on Amazon EKS are provisioned to ensure optimal performance and cost efficiency. Amazon EKS orchestrates the containerized Decloner.ai and FrameInspect.ai processing pipelines, enabling elastic scaling and resilient execution. For high‑throughput video processing, Amazon EC2 with Auto Scaling Groups provides on‑demand compute capacity. Large media assets and derived artifacts are stored durably using Amazon S3, with long‑term archival and cost optimization supported through Amazon Glacier. Event‑driven auxiliary tasks—such as metadata cleanup, orchestration triggers, and batch utilities—are handled using AWS Lambda. End‑to‑end observability and operational monitoring are enabled through Amazon CloudWatch, Prometheus, and Grafana, providing real‑time visibility into system health and performance. Data security and content protection are enforced using AWS KMS for encryption, while secure access, identity management, and governance are implemented through AWS IAM, Single Sign‑On (SSO), and Service Control Policies (SCPs).