Overview

Global Echo, a digital media company, wanted to enable both internal teams and external users, including marketers, agencies, and content creators, to generate engaging videos from natural language prompts. Since their platform was already running on AWS, they needed an AWS-native solution that could integrate text-to-video generation without relying on third-party tools. Bacancy partnered with them to design and implement a scalable solution using Amazon SageMaker, enabling smooth integration within their existing platform, reducing dependencies, and enhancing user experience..

Technical Stack

  • Amazon SageMaker
  • Amazon Bedrock
  • Amazon API Gateway
  • AWS Lambda
  • Amazon S3
  • Amazon EventBridge
  • AWS IAM
  • Amazon CloudWatch

    • Industry

    Entertainment

  • region

    • Region

    USA

  • project-size

    • Project Size

    Non-Disclosable

Highlights

AI-Powered Text-to-Video Generation

Under 3-Minute Video Output

65% Manual Effort Reduction

Content Creation at Speed

AI-Based Prompt Enhancement

Challenges & Solutions

Simple prompts often led to low-quality or generic video outputs

  • Solution: To improve content richness, Our AWS consultants integrated Amazon Bedrock to enhance the prompts before they reached the video model. This prompt enrichment layer leveraged a foundation model (e.g., Claude) to expand short phrases into well-structured, detailed descriptions, leading to higher-quality, more visually aligned outputs.

Need for secure and centralized storage of AI-generated content

  • Solution: All prompts, outputs, and logs were stored in Amazon S3 with encryption and strict IAM policies. This ensured secure access control, automatic versioning, and long-term storage management with lifecycle policies.

Generating short-form videos from plain text in minutes, without manual video editing

  • Solution: Bacancy implemented a pre-trained, open-source generative model using Amazon SageMaker real-time inference endpoints. The model was integrated into the client’s existing platform, enabling users to input natural language prompts and receive AI-generated video clips within minutes. No additional infrastructure or model training was required, significantly accelerating content delivery.

Limited visibility into model usage, performance trends, and cost allocation

  • Solution: Bacancy configured Amazon CloudWatch to monitor real-time AI workload metrics, including video generation latency, model invocation count, success/error rates, and system health. In parallel, AWS Cost Explorer was integrated to break down cost per video generation, daily usage spikes, and projected monthly spend. This helped the client optimize performance, allocate usage by department, and maintain cost control as adoption scaled.

Core Features

  • Real-time AI video generation through Amazon SageMaker
  • Enhanced prompt processing using Amazon Bedrock
  • Seamless UI integration into existing digital platforms
  • Secure, encrypted storage via Amazon S3 and IAM
  • Centralized monitoring of AI performance and cost with CloudWatch and Cost Explorer
  • no.-of-resources

    • No. of AWS Developers

    06

  • time-frame

    • Time Frame

    Feb 2025 - Jun 2025

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