AI Use Case: Building a multi-modal app to extract content from any Document, Image, Audio or Video

In today’s data-driven world, the ability to process multiple types of media—documents, images, audio, and video—is critical for businesses and individuals alike. A multi-modal app that integrates these capabilities offers a powerful solution for managing workflows, improving accessibility, and driving efficiency. Below, we explore specific use cases where such an app can deliver exceptional value.

Building a multi-modal app

Automating Business Workflows

Organizations often juggle separate tools to handle invoices, scanned contracts, and meeting recordings. A multi-modal app simplifies this by:

  • Extracting Text from Documents: Automatically pulling key details like invoice amounts, contract clauses, or compliance data using OCR and natural language processing (NLP).
  • Transcribing Audio Meetings: Converting meeting recordings into searchable text and generating automated summaries for easier documentation.
  • Analyzing Images: Identifying objects in charts or scanned documents to integrate them into reports.

Example: A retail company processes invoices, stock images, and team calls in one app, reducing manual errors by 30% and saving hours of repetitive work.

Media and Content Creation

Creators working with multimedia often spend significant time on transcription, editing, and analysis. A multi-modal app helps by:

  • Transcribing Video Content: Providing accurate captions and searchable text for video editing.
  • Enhancing Images: Automatically cropping, compressing, or stylizing visuals for branding.
  • Summarizing Audio Content: Turning podcast episodes into concise show notes.

Example: A podcaster uses the app to transcribe episodes, generate captions for social media, and create summaries, streamlining production.

Enhancing Accessibility

Inclusive technology ensures content reaches everyone. A multi-modal app supports accessibility by:

  • Providing Real-Time Captions: Making events or meetings accessible to individuals with hearing impairments.
  • Adding Audio Descriptions: Creating audio descriptions for images or videos for visually impaired users.
  • Translating Multimedia Content: Offering multilingual support for global audiences.

Example: A university uses the app to provide lecture transcripts, real-time captions for events, and translations for international students.

Customer Support Optimization

Businesses that handle customer queries across multiple formats benefit greatly from such an app:

  • Analyzing Customer Calls: Transcribing and analyzing sentiment from voice recordings to identify recurring issues.
  • Processing Documents: Automatically verifying IDs and other forms during customer onboarding.
  • Flagging Video Content: Reviewing and moderating user-submitted video clips for compliance.

Example: A financial services company uses the app to process loan applications, transcribe support calls, and verify uploaded documents, cutting response times by 50%.

Educational and Research Support

Educational institutions and researchers often need to manage diverse data sources. A multi-modal app can:

  • Digitize and Organize Notes: Turn scanned handwritten notes into editable, searchable files.
  • Summarize Lectures and Webinars: Transcribe and extract key points from audio or video recordings.
  • Analyze Visual Data: Process charts, graphs, or research diagrams for better understanding.

Example: A researcher digitizes years of handwritten data, transcribes conference recordings, and organizes findings efficiently within a single app.

A multi-modal app that processes documents, images, audio, and video is a versatile tool with applications across industries. From streamlining workflows to enhancing accessibility, it simplifies complex tasks, making it invaluable for businesses, creators, educators, and more.

Building a Multi-Modal App using a Data Machine

  1. Click on the Data Machines navigation menu in the left navigation
  2. Click on Add Data Machine
  3. Drag and drop an Operational Step from the toolbox
  4. Select “Speech-To-Text” from the Audio Category of AI Models
  5. Drag and Drop the Final Step from the toolbox
  6. Configure the options in the Final step based on your need
  7. Test the Data Machine
  8. Publish the Data Machine, if the Test is successful

A template for a multi-modal app is also available in the list Data Machine templates which can easily be cloned.

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