AI Media Analysis | Streamdiver Developer

The Challenge

Video and audio content contains valuable knowledge that is nearly impossible to extract manually. Who spoke when about what? Which topics come up? Which entities are mentioned? Without automated analysis, this information remains hidden.

The Solution

Streamdiver automatically analyzes every uploaded asset: entities, keywords, speakers, OCR text, and more -- all available as structured data via API. Semantic search and chat (RAG) make the knowledge instantly queryable. Flows automate recurring analysis tasks.

6+AI metadata layers per asset

< 1ssemantic search across archives

50+supported languages

Benefits

Structured Data from Media

Every video, audio, and document is automatically analyzed: entities, keywords, speakers, OCR text -- all available as structured data via API.

Natural Language Search

Full-text and semantic search across all media content -- find relevant segments in seconds instead of hours.

Automated Workflows

Flows API for automated summaries, reports, and content generation -- parameterizable and streamable via SSE.

How It Works

Ingest

Upload media via API

AI Analysis

Automatic metadata extraction

Query

Use search, chat, or flows

Export

Retrieve results via API

Features in Detail

Named Entity Recognition for people, places, and organizations

Automatic keyword and topic extraction

Speaker recognition and attribution

OCR text extraction from videos and images

Full-text and semantic search across all content

RAG-based Q&A with source references

Automated AI workflows (Flows) for insights and content generation

Multi-format transcript export (JSON, SRT, DOCX, TXT)

Auto-chapters: AI-based segmentation into thematic sections

Segment-based recommendations for contextually related content

API Integration

AI Analysis via API

Full programmatic access to all AI analysis results -- from metadata to automated workflows.

Metadata Extraction

Retrieve entities, keywords, speakers, OCR, and document content as structured data.

Full-Text & Semantic Search

Keyword-based and natural language search across your entire media library.

Chat & RAG

Natural language questions against media content -- answers with source references and timestamps.

Flows API

Parameterized AI workflows for summaries, reports, and automated content generation.

Transcript Export

Export transcripts with speaker attribution as JSON, SRT, DOCX, or TXT.

Auto-Chapters

AI segments videos automatically into thematic sections – the foundation for navigation, search, and recommendations.

Recommendation API

Recommend contextually related content at the section level – based on metadata, transcripts, and tags.

# 1. Erkannte Entitäten, Keywords und Sprecher abrufen
curl "https://api.streamdiver.com/v2/media/{assetId}/metadata?expand=entities,keywords,speakers" \
  -H "Authorization: Bearer YOUR_TOKEN"

# 2. Semantische Suche über alle Medien
curl "https://api.streamdiver.com/v2/search/semantic?text=Welche%20Entscheidungen%20wurden%20getroffen" \
  -H "Authorization: Bearer YOUR_TOKEN"

# 3. KI-gestützte Frage (RAG)
curl -X POST https://api.streamdiver.com/v2/chats \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Fasse die wichtigsten Punkte zusammen", "mediaIds": ["{assetId}"]}'

# 4. Flow ausführen (z.B. Meeting-Zusammenfassung)
curl -X POST https://api.streamdiver.com/v2/flows/{flowId}/runs \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Accept: text/event-stream" \
  -d '{"mediaId": "{assetId}", "llmProvider": "streamdiver/nitrox", "params": {"language": "de"}}'

Integration Flow

Upload mediaS3 API

AI analysisWebhook

Retrieve metadataREST API

Search & ChatSemantic + RAG

Ready to get started?

Schedule Demo Documentation