EndorsedendorsedCompleted

Cloud Video Analysis Platform & Scalable Transcoding Engine

Services Covered:

Custom Software Development
Project hero — replace with case study imagery
Industry
Industry

Information Technology

Duration
Duration

24 months

Budget
Budget

50K - 199K

Client Size
Start Date

1 January 2015

Team Size
Team Size

6-10 Employees

Engagement Model
Engagement Model

Onshore

Project Capability Score (PCS)

gauge meter
74/100
Good

Project Capability Score (PCS) estimates how capable ScrumLaunch is of successfully delivering a project like this, based on its past experience, track record, and ability to handle similar work. Learn more about PCS


Client

vLoop

mapLos Angeles, United States of America

Project Summary

ScrumLaunch built a responsive Angular web application and a scalable video transcoding engine (Go, Python) for a cloud-based video analysis platform. They transcoded many input formats to web-friendly outputs (MP4, HLS, WebM) and optimized AWS CPU usage to reduce costs. The platform scaled to hundreds of thousands of hours of uploaded video and attracted thousands of users, including professional, college, and high school sports teams. The vendor integrated into remote scrum processes and provided strong communication and access to the development team.

Key Challenges

  • Needed development assistance to build a cloud-based video analysis platform and transcoding engine.
  • Required a responsive frontend for interacting, clipping, editing, commenting, and annotating video.
  • Wanted to enable sports teams of all levels to use video to improve performance.

Project Deliverables

  • Responsive Angular web application
  • Scalable video transcoding engine built in Go and Python
  • Transcoding pipeline supporting MTS, MOV, WMV, AVI to MP4, HLS, and WebM
  • Frontend co-refactoring and AWS CPU optimization

Project Solution

ScrumLaunch delivered a dedicated engineering team that built a responsive Angular web application enabling users to interact with, clip, edit, comment on, and draw annotations in video. They architected and implemented a scalable transcoding engine in Go and Python to convert nearly any input format (MTS, MOV, WMV, AVI) into web-friendly outputs (MP4, HLS, WebM). The team co-refactored the frontend and optimized AWS CPU usage to lower transcoding costs and support large-scale uploads.

Project Outcome

  • Gained thousands of users, including professional, college, and high school sports teams.
  • Platform usage included teams featured in the Olympics and on television.
  • Optimized AWS CPU usage to reduce transcoding costs.
  • Smooth remote scrum process with direct access to developers and effective communication.

Platforms

  • WebWeb

Tech Stack

  • AngularAngular
  • GoGo
  • PythonPython
  • Amazon Web Services (AWS)Amazon Web Services (AWS)

Client Endorsement

Overall Review Rating

4.88star5 out of 5 stars

Timeliness

Cost Rating

Willing to Refer

Quality of Deliverables

The successful launch of the platform drew thousands of new users. ScrumLaunch also optimized CPU usage to reduce transcoding costs. Expect an accessible and responsive partner who can integrate into scrum processes remotely in order to understand and meet coding requirements.

Tony Lambropoulos

VP of Engineering

Note: This endorsement is based on publicly available client feedback from external review sources.

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