Media Upload: Intelligent Content Ingestion

Media Upload: Intelligent Content Ingestion

Transform any media file into AI-ready, searchable content with intelligent upload processing that automatically extracts, analyzes, and indexes documents, images, audio, and video.

The Content Ingestion Challenge

Organizations drown in unstructured content:

• Document chaos: PDFs, Word docs, presentations, spreadsheets scattered across systems
• Media silos: Images, videos, and audio files stored without meaningful metadata
• Search limitations: Content exists but can't be found
• Manual processing: Hours spent extracting information from files
• Format fragmentation: Different tools for different file types

The result: valuable content becomes invisible, searchable only by filename or manual tags. Knowledge workers spend 30% of their time searching for information they know exists somewhere.

Intelligent Media Processing

Media Upload transforms raw files into structured, searchable, AI-accessible content---automatically extracting text, metadata, entities, and meaning from any file type.

Universal Format Support

Documents:

• PDF (text, scanned, forms)
• Microsoft Office (Word, Excel, PowerPoint)
• Google Workspace formats
• Plain text and Markdown
• ePub and eBooks

Images:

• JPEG, PNG, WebP, TIFF
• RAW camera formats
• Screenshots and graphics
• Scanned documents
• Infographics and diagrams

Audio:

• MP3, WAV, FLAC, M4A
• Podcasts and recordings
• Voice memos and dictation
• Call recordings
• Audiobook files

Video:

• MP4, MOV, AVI, MKV
• Screen recordings
• Webinars and presentations
• Social media clips
• Surveillance and monitoring

Intelligent Extraction

Every upload triggers comprehensive analysis:

Text extraction:

• OCR for scanned documents and images
• PDF text layer extraction
• Presentation slide content
• Spreadsheet data parsing

Speech-to-text:

• Audio transcription with speaker identification
• Video audio track processing
• Timestamp alignment
• Language detection and translation

Visual analysis:

• Object and scene recognition
• Face detection and identification
• Text in images (signage, labels)
• Document layout understanding

Metadata enrichment:

• Entity extraction (people, places, organizations)
• Date and event detection
• Topic classification
• Sentiment analysis

Knowledge Graph Integration

Extracted information flows into your organization's knowledge graph:

Entity linking: Connect extracted entities to existing knowledge Relationship mapping: Identify connections between content and concepts Semantic indexing: Enable natural language search across all content Version tracking: Maintain history of content changes

Processing Pipeline

1. Upload

• Drag-and-drop or API ingestion
• Batch upload for large collections
• Cloud storage integration (S3, GCS, Azure)
• Email attachment capture
• Web clipper extension

2. Analyze

• File type detection and routing
• Content extraction (text, audio, visual)
• Metadata generation
• Entity recognition and linking
• Quality assessment

3. Index

• Full-text search indexing
• Vector embedding generation
• Knowledge graph integration
• Access control application
• Thumbnail and preview generation

4. Access

• Search across all content types
• AI-powered Q&A over your content
• API access for applications
• Export and sharing
• Usage analytics

Use Cases

Document Intelligence

Scenario: Legal team receives thousands of contracts requiring review.

Media Upload delivers:

• Automatic contract type classification
• Key clause extraction (terms, parties, dates)
• Risk flag identification
• Searchable archive with full-text access
• Entity linking to matter management

Result: 80% reduction in document review time.

Meeting Intelligence

Scenario: Organization records hundreds of meetings but content is lost after the call.

Media Upload delivers:

• Automatic transcription with speaker labels
• Action item extraction
• Decision documentation
• Searchable meeting archive
• Integration with calendar and project management

Result: Meetings become searchable institutional knowledge.

Research Content

Scenario: Research team accumulates papers, reports, and data files across projects.

Media Upload delivers:

• Multi-format ingestion (PDFs, data files, images)
• Citation and reference extraction
• Topic clustering and organization
• Cross-reference discovery
• Research knowledge graph building

Result: Research builds on institutional knowledge, not individual memory.

Customer Communications

Scenario: Support team handles emails, chat transcripts, and call recordings.

Media Upload delivers:

• Unified ingestion across communication channels
• Sentiment and urgency detection
• Issue categorization
• Customer history building
• Knowledge base article generation

Result: Complete customer context for every interaction.

Platform Capabilities

Processing Dashboard

• Upload status and progress
• Processing queue management
• Error handling and retry
• Quality metrics and reports

Search Interface

• Full-text search across all content
• Filter by type, date, entity, source
• Natural language queries
• Saved searches and alerts

API Access

• RESTful upload endpoints
• Webhook notifications on completion
• Query API for search and retrieval
• Bulk operations for large collections

Admin Controls

• Access permissions by content and user
• Retention policies and archiving
• Usage monitoring and quotas
• Audit logging

Technical Specifications

Processing Capacity

• Up to 10GB per file
• 1,000+ concurrent processing jobs
• Sub-second latency for small files
• Predictable throughput for large batches

Accuracy Metrics

• OCR accuracy: 95%+ on clear documents
• Transcription accuracy: 90%+ on clear audio
• Entity extraction: 85%+ F1 score
• Classification accuracy: 90%+ on trained categories

Integration Options

• REST API with comprehensive documentation
• SDKs for Python, JavaScript, Java
• Zapier integration for no-code workflows
• Enterprise SSO (SAML, OAuth)

Pricing

Volume-based pricing by processing units:

Processing unit costs:

• Documents: 1 unit per 10 pages
• Images: 1 unit per 10 images
• Audio: 1 unit per 10 minutes
• Video: 2 units per 10 minutes

Integration with Nexus Platform

Media Upload serves as the content ingestion layer for the Adverant Nexus platform:

GraphRAG integration: Extracted entities and relationships flow into your knowledge graph FileProcessAgent: Advanced document analysis and extraction VideoAgent: Deep video content analysis and scene understanding Memory system: Content becomes part of organizational long-term memory

The Content-to-Knowledge Pipeline

Raw files are just containers. The value is in the knowledge they contain. Media Upload transforms content from:

Opaque files → Searchable text Isolated documents → Connected knowledge Manual processing → Automatic extraction Lost content → Accessible intelligence

Stop filing. Start finding.

[Start Processing Your Content →](/contact?module=media-upload)

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Media Upload is included with Nexus platform subscriptions. Standalone processing available for integration with other systems.