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Stop building fragile video pipelines

Get clean, structured,
vector-ready data
from videos in minutes.

Built for startups that need to analyze large video libraries without expensive tools or custom pipelines.

Start with $5 free credit

Test with your own videos immediately after approval.

Powering The Next Generation of Video Search

PineconeWeaviateQdrantOpenAILangChainHuggingFaceLlamaIndexChromaDBSupabaseMilvusPineconeWeaviateQdrantOpenAILangChainHuggingFaceLlamaIndexChromaDBSupabaseMilvus

Live RAG Demo

Select a video and ask semantic questions to see vector search in action.

This is a classic keynote from Steve Jobs introducing the iPhone in 2007.

You can ask questions like:

  • "What were the key features of the first iPhone?"
  • "How did Steve Jobs describe the user interface?"
Youtube HD Player•Dynamic Semantic Segmentation
Pinecone Indexed•OpenAI Embeddings

Vector-Vid API Workflow

From raw video files to RAG-ready embeddings in ~30 seconds.

01

Upload Video(s)

  • Any format (mp4, mkv, mov)
  • Any size
  • Mixed libraries
02

Vector-Vid Processing

  • Video understanding
  • Context-aware chunking
  • Metadata extraction
  • Structured JSON output
03

Receive JSON

  • Clean, RAG-ready data
{
  text_chunks,
  timestamps,
  metadata
}
04

Push to Vector DB

  • Pinecone
  • Weaviate
  • FAISS
  • Any vector store
05

AI Agent Uses It

  • Accurate answers
  • Video-aware context
  • Precise timestamps

No custom pipelines. No manual cleanup.
Just structured data your AI can use.

Developer Note: Zero Vendor Lock-in

Vector-Vid does not lock you into a proprietary vector database. You own the embeddings and storage. We just provide the clean JSON output for you to store wherever you want (Pinecone, Weaviate, Postgres, etc.).

Structured Intelligence, Delivered via API

Get granular video understanding with scene-by-scene breakdowns, visual descriptions, and perfect timestamps.

1[
2  {
3    "chunk_id": "vid01_chunk01",
4    "video_title": "Macworld 2007 Keynote",
5    "start_time": "00:00:00",
6    "end_time": "00:00:34",
7    "chunk_summary": "In a dramatic keynote moment, Steve Jobs, illuminated against a dark backdrop, enthusiastically declares the anticipation of a revolutionary product—likely the iPhone—while the iconic Apple logo bursts forth from a radiant blue-white light on a massive screen.",
8    "captions": "this is a day i've been looking forward to for two and a half years [Applause] every once in a while a revolutionary product comes along that changes everything...",
9    "visual_narrative": "Image Summary: A striking, high-contrast shot captures a pivotal moment from a technology keynote presentation. The composition is split into two main focal points: on the left, a presenter stands in profile, illuminated against the darkness, while on the right, a massive screen displays a graphic. The graphic features the iconic Apple logo silhouetted against a radiant, celestial burst of blue-white light..."
10  },
11  {
12    "chunk_id": "vid01_chunk02",
13    "video_title": "Macworld 2007 Keynote",
14    "start_time": "00:00:35",
15    "end_time": "00:00:46",
16    "chunk_summary": "In a darkened keynote presentation, Steve Jobs stands beside a large projection of the original Macintosh from 1984, emphasizing its transformative impact on technology.",
17    "captions": "it's been able to introduce a few of these into the world 1984 we introduced the macintosh it didn't just change apple",
18    "visual_narrative": "Image Summary: The image captures a scene from an Apple keynote presentation featuring Steve Jobs standing on a dark stage to the left of a large projection screen. The screen displays a high-fidelity image of the original Macintosh computer against a gradient blue background, accompanied by the year '1984' in white text..."
19  },
20  {
21    "chunk_id": "vid01_chunk03",
22    "video_title": "Macworld 2007 Keynote",
23    "start_time": "00:00:47",
24    "end_time": "00:00:50",
25    "chunk_summary": "As the speaker claims, 'it changed the whole computer industry,' the visuals of the iconic 1984 Macintosh computer underscore its revolutionary impact.",
26    "captions": "it changed the whole computer industry",
27    "visual_narrative": "Image Summary: The image showcases a historical piece of computing technology, the original Apple Macintosh computer, against a dark, graduated background. The computer is a beige, all-in-one desktop unit with a built-in CRT monitor, a detached mechanical keyboard, and a wired rectangular mouse..."
28  },
29  {
30    "chunk_id": "vid01_chunk04",
31    "video_title": "Macworld 2007 Keynote",
32    "start_time": "00:00:51",
33    "end_time": "00:00:53",
34    "chunk_summary": "Steve Jobs walks across the stage against a dramatic backdrop featuring a large image of the original 1984 Macintosh.",
35    "visual_narrative": "Image Summary: This wide-angle, medium-shot photograph captures a significant moment from a technology keynote presentation, featuring Steve Jobs on stage in a large, dimly lit auditorium. The scene is dominated by a massive projection screen displaying the original 1984 Macintosh computer..."
36  }
37]
JSONUTF-8

Integration Ready For

PineconeWeaviateQdrantChromaDBMilvusPostgres (pgvector)

Why Not Build This Yourself?

You can — but here’s the real cost.

Building In-House

The Engineering Burden

  • Handling multiple video formats & codecs
  • Building segmentation logic from scratch
  • Context-aware chunking algorithms
  • Managing GPU infrastructure

The Business Risk

  • Missed client deadlines
  • Engineers maintaining glue code
  • Fragile pipelines that break often

Vector-Vid Instead

What you get immediately

  • Plug-and-play API Integration
  • Predictable token-based pricing
  • Production-ready clean JSON output
  • Zero pipeline maintenance
  • Enterprise-grade reliability

Ship features, don't babysit pipelines.

Most teams don’t fail because they can’t build this — they fail because it’s not worth building.

Built for Real-World Applications

Give your AI the context it needs to understand video content.

SaaS Help Centers

ProblemAnswers trapped in long onboarding videos.
SolutionInstant 'Chat with Support' bots.

EdTech Platforms

ProblemStudents can't Ctrl+F specific diagrams in video materials.
SolutionSearchable visual segments for retrieval.

Sales Intelligence

ProblemManagers missing 'Pricing' context in daily video calls.
SolutionQuery specific moments across all demos.

Internal Knowledge

ProblemTown halls are black boxes employees ignore.
SolutionMake every internal video recording RAG-ready & searchable.

Dev Tools & Infra

ProblemBuilding video pipelines is heavy & expensive.
SolutionOne API for embedding-ready chunks, focus on your workflow and UI.
Launch Offer

Get Early Access &
$5 in API Credits

Join the waitlist today to lock in your credits. We onboard new developers each week.

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Turn your video library into RAG-ready vector embeddings. Search, analyze, and chat with your video content in milliseconds.

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