EXMIONAMAMI
AI SPORT ↗
PlatformAI Media Asset Management InfrastructureCore engineSemantic Media Intelligence Engine
Next-generation media asset management

Turn every media asset into searchable intelligence

AMAMI is a next-generation media asset management system built on the Semantic Media Intelligence Engine. It transforms processed video libraries into clear, searchable knowledge with direct access to every source frame.

Explore capabilities
● The archive is processed and ready to explore◎ Verifiable answers linked to source material
REAL PROCESSED SOURCE● READY
NASA · ASR + OCR + ENTITIES + OBJECTS

Space Operations.mp4

Play the actual archive source, then open its synchronized analysis.

2Real processed videos
302Timecoded speech excerpts
52OCR fragments
100%source-linked
Live demonstration

Try real processed archive materials

These are the same full source videos used inside AMAMI. Every result remains connected to the original frame and timecode.

REAL VIDEO · 6:46
NASA / ASTROBIOLOGY

Space Operations.mp4

NASA Launch Pad explains astrobiology, methane on Earth and Mars, spectroscopy, and the search for signs of life beyond Earth.

155 speech excerpts20 OCR10 entities10 objects
REAL VIDEO · 5:58
NASA / ASTRONOMY

What Is the Solar System.mp4

NASA Our World explains the Solar System, the planets orbiting the Sun, and how astronomers classify planets, moons, asteroids, meteors, and comets.

147 speech excerpts32 OCR13 entities10 objects
Capabilities

What AMAMI can do

A workspace for finding, verifying, and reusing media materials.

01

Semantic search

Finds exact keywords and semantically related excerpts in speech and on-screen text.

02

Source-grounded AI assistant

Generates concise answers only from archive materials and shows supporting excerpts.

03

Faces, objects, and locations

Groups faces, recognizes objects, and helps locate every appearance across materials.

04

Transcription and OCR

Synchronizes speech, on-screen text, and timecodes for fast source verification.

05

Relationship graph and dossiers

Shows co-mentions between people, organizations, places, and related video excerpts.

06

Project collections

Combines important excerpts from different files into one thematic story.

How it works

From archive to evidence in three steps

01

Open the processed archive

Materials already contain transcripts, OCR, faces, objects, and extracted entities.

02

Find the right context

Use Ask AMAMI, the graph, or entity dossiers depending on your research task.

03

Verify the source

Open the found excerpt at the exact timecode and save it to a working collection.

Built for

One archive, multiple workflows

AMAMI accelerates discovery and verification wherever video is a critical source of knowledge.

01

Newsrooms and broadcasters

Find soundbites, people, and events across years of broadcast footage.

02

Enterprise media libraries

One search layer for interviews, conferences, learning content, and internal video.

03

Production and research

Build verifiable collections and return to the source in one step.

Data control

Runs where your archive lives

AMAMI can run on-premises or in a private cloud. Source media remains under your control, and every answer links back to supporting evidence.

On-premisesPrivate cloudRole-based accessVerifiable sources
Interactive media archive

Ready to try AMAMI?

Open the demo archive and follow the built-in step-by-step tutorial.