MediaMind
JPGcoast-at-dusk.jpg
YOUR MEDIA. YOUR DEVICE. YOUR RULES.
Every memory.
One search away.
Search all your media with text, images, or voice.
Powered by Google EmbeddingGemma 2. Local-first multimodal search, built to keep your private world private.
Early access coming soon. No credit card needed.
Your library, rediscovered.
✦Golden hour by the ocean↵
Curated sample matchesAll media
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00:24weekend-escape.mp4
02:18
ocean-ambience.wav
Notes from the coast
The light softens. The horizon blurs. A place worth coming back to.
field-notes.pdf
Try a search mode. These are curated sample results, not a live AI search.
A preview of what’s possible. Your files stay yours.EmbeddingGemma 2
BUILT ON OPEN INTELLIGENCE
Google EmbeddingGemma 2
Native multimodalLocal embeddingsPrivate by design
An independent product. Not affiliated with or endorsed by Google.
LESS SEARCHING. MORE FINDING.
Your entire library. Finally connected.
Files have names. You remember moments. MediaMind is being built to bridge the gap.
One search. Every format.
Find photos, video moments, voice notes, and documents in one shared semantic space.
NATIVELY MULTIMODALIntelligence stays local.
EmbeddingGemma 2 is designed for on-device use. Index and search on your own hardware.
LOCAL EMBEDDINGPrivate means private.
Our product design keeps your media and its embeddings on your device. Your library is never training data.
YOUR DEVICE, YOUR DATASmall footprint. Big ideas.
A compact, modular model for everyday devices. Mobile support is planned; performance depends on hardware.
BUILT FOR THE EDGEA knowledge base in a click.
Bring scattered files into a private knowledge base. No manual tagging or perfect filenames required.
LESS ORGANIZINGFrom finding to understanding.
On the roadmap: local RAG with Gemma 4, for answers grounded in your own media and documents.
ON THE ROADMAPFROM FOLDERS TO ANSWERS
Three steps. All on your device.
The experience we’re building, from import to discovery.
Bring your media
Add images, videos, audio, and documents from your device. No cloud upload required.
Make it searchable
EmbeddingGemma 2 creates local embeddings, connecting files by what they mean.
Find it your way
Describe a moment, use a reference image, or ask with your voice.
On-device by designEmbeddingGemma 2No media uploads
MADE FOR YOUR KIND OF MIND
Good ideas deserve to be found again.
For creators
Find that perfect clip, forgotten reference, or sound that completes the story.
“That golden-hour shot by the ocean”
For knowledge workers
Connect notes, research, screenshots, and recordings into your personal memory.
“The diagram from my research on local AI”
For privacy-conscious teams
Explore local discovery for sensitive material. Team collaboration is a future direction.
“The concept from our last design review”
EARLY ACCESS
Start with curiosity. We’ll take care of the invite.
Joining the waitlist is free. Product pricing will be announced before launch, with no commitment to purchase.
Pricing for the product is coming soon.
- Be notified when early access opens
- Receive occasional product updates
- Help shape what comes next
What is EmbeddingGemma 2?
EmbeddingGemma 2 is Google’s open multimodal embedding model. It maps text, images, audio, and video into a shared vector space, so different types of media can be compared by meaning. MediaMind plans to use it for local semantic search.
What makes multimodal search different?
You can find an image with a sentence, a video moment with a reference image, or related files with voice. The planned experience connects formats through meaning instead of relying only on filenames or tags.
Does my media leave my device?
The planned MediaMind app will generate and store embeddings locally, without uploading your media to Google or other third parties. This website is a marketing preview: it does not accept media. The waitlist sends only your email, language, and consent record to our hosting and storage provider.
Can EmbeddingGemma 2 run on a phone?
Google designed the model for consumer devices, including phones and laptops. MediaMind’s mobile support is planned, and actual requirements will depend on model configuration and your hardware. We will publish supported devices after testing.
How is a local embedding different from a cloud API?
A local embedding is generated on your device after the model has been downloaded. Media files do not need to be sent to an embedding API. Initial installation and model downloads require a connection; offline search is part of our product design.
Will MediaMind support Gemma 4 and local RAG?
Yes, this is on the roadmap. EmbeddingGemma 2 would retrieve relevant files, and Gemma 4 would help answer questions using that context. This is a planned integration, not a feature available in this preview.
Can I use MediaMind today, and what will it cost?
MediaMind is in pre-launch development. The interactive preview uses sample media and does not run an AI model. Join the free waitlist for launch news. Product pricing and the release date have not been announced.
YOUR NEXT GREAT FIND STARTS HERE
A little less lost. A lot more possible.
Be first to discover a more private way to search.
We store your email for the waitlist. No media is collected. Privacy notice