AI Launch Profile
note.md Local LLM Memory
note.md launched a local-first Mac research workspace update that turns cited notes and documentation into local LLM memory for search and research workflows.
At a glance
Launch Snapshot
- Company
- ARSoftware
- Launch date
- June 26, 2026
- Launch type
- Not classified
- Category
- AI Productivity Tools
- Audience
- Researchers, students, and writers who want private local-AI search across papers, citations, and markdown notes on Mac.
- Pricing
- Not publicly confirmed
- Free plan
- Not publicly confirmed
- API
- Not publicly confirmed
- Open weights/source
- Not publicly confirmed
Launch Context
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Verification & Sources
- Status
- Verified
- Source links
- 4
- Freshness
- Verified July 9, 2026
- Last verified
- July 9, 2026
- Last updated
- July 9, 2026
Key source checks
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Kingy Launch Score
6.4 / 10 · Mixed
One earned credibility score, computed from cited evidence — not a placeholder. How the Kingy Launch Score works
Why this score
- Source & verification 7.5/10 — Official product, pricing, and about pages plus a dated Product Hunt listing — mostly first-party with one third-party record. notemd.org
- Product evidence 7.0/10 — A shipped, downloadable Mac app with product and about pages; no repository or API docs. notemd.org
- Significance & novelty 5.0/10 — Local-first research search that turns cited notes into LLM memory — useful but niche, Mac-only research workflows. notemd.org
- Traction signals 5.0/10 — A dated Product Hunt listing is a checkable third-party launch signal; no adoption metrics are cited. producthunt.com
- Offer clarity 7.0/10 — An official pricing page documents the access model. notemd.org
Evidence checked 2026-07-10
Creator Coverage Next Steps
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Kingy AI Take
note.md launched a local-first Mac research workspace that turns cited notes and documentation into local LLM memory for private search, with a public pricing page and a dated Product Hunt listing (notemd.org). Researchers, Students, and Writers who want semantic search without sending papers to a cloud model are the fit. Local-model performance and export behavior vary by machine, so confirm both and current App Store pricing before importing a large library.
Who it is for
Researchers, students, and writers who want private local-AI search across papers, citations, and markdown notes on Mac.
Source-backed record