ScriptMatch is a fully serverless, Azure-native platform that recommends movies based on what's actually said in them — not just their genre or manual tags. It uses AI to transcribe movie audio, extract meaningful keywords from the dialogue, and match films that share similar narrative content.
Traditional movie recommendation systems rely on broad genre labels and manually assigned tags. This approach is slow, inconsistent, and misses the richest source of information a movie has — its actual dialogue. ScriptMatch fixes this by automatically analyzing what characters say, extracting key vocabulary, and using that to surface genuinely similar films.
A movie is uploaded to Azure Blob Storage. This automatically triggers Azure Event Grid, which kicks off the processing pipeline via Azure Logic Apps — no manual intervention needed.
Azure AI Video Indexer processes the video and extracts:
- Full transcripts
- Keywords and topics
- Sentiment signals
Each movie ends up with a rich semantic metadata profile built entirely from its content.
The extracted keywords and metadata are stored in Azure AI Search, making every movie fully searchable and comparable by content rather than category.
When a user watches a movie, their taste profile is updated in Azure Cosmos DB — tracking the genres and keywords they engage with. ScriptMatch then computes similarity between movies (and users) based on shared keyword patterns, surfacing recommendations that are genuinely content-driven.
| Service | Role |
|---|---|
| Azure Blob Storage | Stores uploaded video files |
| Azure Event Grid | Detects uploads and triggers workflows |
| Azure Logic Apps | Orchestrates the processing pipeline |
| Azure AI Video Indexer | Transcribes audio and extracts keywords |
| Azure AI Search | Indexes and queries movie metadata |
| Azure Functions | Runs all backend logic (fully serverless) |
| Azure Web App | Hosting web applications, APIs, and mobile backends |
- Backend — Node.js with Express
- Frontend — HTML, CSS, Vanilla JavaScript
- Cloud — Microsoft Azure (fully serverless, no containers or VMs)
| Name | GitHub |
|---|---|
| Reenu L K | ReenuLK |
| Krishna Deepak | krisndeep |
| Yogini Aishwaryaa P T S | yoginiaishwaryaa |