Multimodal AI search for Mac, indexing local video, audio, and documents.
Product memo
GoldenRetriever.ai helps Mac users navigate large, unsearchable media libraries. It applies multimodal AI to understand video, audio, and document content directly, moving beyond simple transcripts. The tool indexes files locally, keeping them off the cloud, and lets users ask questions in plain English to get timestamped answers.
For who
Mac users with large media libraries
Solves what
Finding specific moments in videos, audio, and documents using multimodal AI.
- Multimodal AI search
- Local file indexing
- Timestamped sourced answers
In their own words
Every video, every file, searchable by meaning – and visual context.
Index your Mac, external drives, and shared volumes. Videos, audio, PDFs, decks, screenshots, scans — understood by multimodal AI, searchable by meaning in plain English (even if it's in Japanese). Your files never leave your control.
Your files never leave your control.
Commercial cues
Model
subscription
Free tier
Yes
Trial
Available
Pricing Strategy
- • Founding-member pricing locks in lower rates for early adopters.
- • Free tier lowers testing friction.
Operator context
Operating setup
Founded
May 2026
Platform
Desktop
Audience
General
Social footprint
Builder Strategy
- Strategy Type
- Niche Specialist
- Stage
- Pre Revenue
- Effort
- Small Team
About GoldenRetriever.ai Public Beta Expand
GoldenRetriever.ai provides a specialized search experience for Mac users managing extensive collections of video, audio, and document files. It moves beyond keyword matching by using multimodal AI to understand the context within media, allowing users to ask natural language questions and receive precise, timestamped answers.
This local-first indexing approach ensures that files remain on the user's device, addressing privacy concerns often associated with cloud-based AI products. The product's positioning targets professionals and power users who need to quickly retrieve information from their personal or work archives without uploading sensitive data.