Dictly – Local, real‑time voice‑to‑text for macOS (sub‑100ms, no cloud)
TL;DR: I built a native macOS dictation app that transcribes locally and instantly. Text appears as you speak (measured ~100 ms first‑character latency). No accounts, no servers, no tracking. Links: • Website: https://dictly.app • Mac App Store: https://apps.apple.com/de/app/dictly-no-keys-just-clarity/id... • Free download; optional Pro tier (pipelines, unlimited history, etc.) What it does Real‑time transcription — streaming text while you talk, not after you stop. Quick‑Capture Overlay (macOS) — global hotkey, drop text into any app/field.…
In plain words
Dictly is a native macOS voice-to-text application that transcribes speech locally in real-time, displaying text as the user speaks with approximately 100 milliseconds latency. It requires no cloud services, accounts, or tracking. The app includes a global hotkey overlay for quick capture into any application, custom processing pipelines, and dictionary profiles for domain-specific terms. A free version is available with optional Pro features for advanced pipelines and unlimited history.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
TL;DR: I built a native macOS dictation app that transcribes locally and instantly. Text appears as you speak (measured ~100 ms first‑character latency). No accounts, no servers, no tracking. Links: • Website: https://dictly.app • Mac App Store: https://apps.apple.com/de/app/dictly-no-keys-just-clarity/id... • Free download; optional Pro tier (pipelines, unlimited history, etc.) What it does Real‑time transcription — streaming text while you talk, not after you stop. Quick‑Capture Overlay (macOS) — global hotkey, drop text into any app/field. Custom Pipelines — local post‑processing steps for cleanup, punctuation, or house style. Dictionary Profiles — teach domain terms (names, brands, code tokens, etc.). Local Analytics — see time saved vs typing (computed on device, never sent anywhere). Why I built it I wanted dictation that felt as immediate as typing and was trustworthy. Most tools stream audio to a server; I wanted something that never leaves the machine. How it’s built (high‑level) Swift + Apple speech/ML frameworks. Streaming audio capture → on‑device recognition → local pipeline → paste into the active app. Works with Wi‑Fi off; there are no network requests in the transcription path. What’s different vs built‑ins Always on‑device + streaming with a global overlay that works in any app. Extensible, deterministic cleanup via pipelines (not a black‑box cloud). Per‑project dictionaries to tame jargon and proper nouns. Numbers (early) Latency: ~100 ms (first visible characters from speech onset) in typical conditions on modern Macs. Privacy: zero telemetry; no account; no background syncing. Everything stays local. Trade‑offs (calling them out up front) Accuracy depends on mic and environment (no surprise). For weird proper nouns/jargon, you’ll want a dictionary profile. Heavy background noise will degrade results (pipelines can only do so much). What I’m looking for from HN Performance impressions on different hardware. Failure cases (accents, acronyms, coding, meetings). Pipeline ideas you’d actually use (e.g., Markdown formatting, code‑block guards, style rules). Integration wishes: CLI? Shortcut actions? Editor‑specific helpers? I’m a solo dev. Happy to answer pointed questions and ship fixes fast. If you spot hand‑wavy claims, call them out.
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