What would you like your AI agent to do? We will take it from there.
Talk to an Expert

Case study

Video Recommendation System for a Communication and Personal Development Application5.0 rating5 Stars Rated On Clutch

Industry

Education & EdTech

Services Used

Artificial Intelligence (AI), Computer Vision

Region

Australia

Engagement Model

Joint Product Development Framework

Function/Department

IT and Technology Support

About Client

  • An AI-powered communication and personal development coach for mobile devices.
  • The mobile application has a repository of thousands of videos from internationally recognized coaches. The videos are shown as per the goals and interests set by the users.
Objectives
To recommend relevant and engaging videos to users based on their interests and goals.

Problem STATEMENT

  • Multiple data sources and insufficient data resulted in a cold start problem.
  • The system was designed in such a way that it uses only metadata and some rules for the recommendation engine. This was a limiting factor as we cannot capture the whole essence of the information.
  • Feature extraction was difficult due to the large size of the videos.

Solution

The steps that we followed to execute our solution were as follows:
  • We applied a hybrid multi-model base system for recommending videos by analyzing the metadata of videos, users, and the content type or categories.
  • We created a system that required the users to mention the skills they want to enhance (personal, interview, managerial, or leadership skills). These data points were used to build the recommendation system. Moreover, we created a repository of videos that are most watched by users based on the information gathered such as geographical location, demographic, etc.
  • The system included a neural network-based filtering algorithm that utilizes users’ metadata and app usage history. This enabled the app to recommend videos to users based on the preferences of other users with similar interests and activities.
  • For new videos uploaded into the system, we collected information based on the most active users who watched almost all the videos. The new videos were then recommended to these active users to gauge whether the video would be accepted by other users or would they lose interest. Based on the video content and quality information gathered, the videos were recommended to other users.

Business Impact

You saw how we solved their business problem. We can do the same for you.

Submit your details & our experts will reply you with a quote very soon.

Your information is kept secure and confidential. We respect your privacy and will not share your data with third parties without your consent.

Frequently Asked Questions(FAQs)

How do I know if a solution like this is right for my business?

A solution like this is a good fit if your teams spend more time collecting and reconciling data than acting on it, if reports from different departments do not match, or if decisions depend on delayed or manual reporting. It also fits when your data is growing in volume or sources, and your current setup struggles to keep up.

DataToBiz starts with a discovery call to review your goals, data sources, and reporting gaps. You get a clear view of the expected outcomes, effort, and timeline before any commitment.

Can DataToBiz customize the solution for my industry and current data setup?

Yes. Every solution DataToBiz delivers is configured around your industry, business processes, and existing data environment. The team assesses your current systems, data quality, and reporting needs first, then designs a solution that works with what you already have instead of replacing it. This applies across industries such as manufacturing, retail, healthcare, finance, and logistics, and across setups ranging from legacy databases to cloud data platforms.

Which tools, platforms, and data sources does DataToBiz work with?

DataToBiz works across the major analytics, cloud, and data engineering stacks. For BI and visualization, this includes Power BI, Tableau, and Looker. For cloud platforms, it includes Microsoft Azure, AWS, and Google Cloud. For data warehousing and processing, it includes Snowflake, Databricks, and SQL-based databases. Data sources include ERP and CRM systems, spreadsheets, APIs, IoT and sensor data, and third-party applications.

If your stack includes a tool not listed here, the team can assess compatibility during discovery.

How long does a project like this take with DataToBiz?

Most projects with DataToBiz take from a few weeks to a few months. The timeline depends on how ready your data infrastructure is for the initiative and how many systems need to connect. Smaller solutions go live quickly, while larger programs roll out in phases so you see value early. After an initial discovery call, you receive a timeline with clear milestones.

How does DataToBiz keep my data secure and compliant during the entire engagement?

Security and governance is part of the plan from the first conversation. DataToBiz works within your security policies and follows the regulations that apply to your industry. The project usually Access stays limited to the people who need it, and confidentiality terms cover the engagement from kickoff to handover.

What support and results can I expect after the solution goes live?

The work does not stop at go-live. Your team gets a proper handover and guidance on using the solution, and DataToBiz stays available for questions and improvements. The business impact of the project is measured against the goals set at the start, so you can see exactly what changed for your company.

DMCA.com Protection Status