Hyprnote

What do they actually do

Hyprnote is an open-source, desktop-first notetaker that records and transcribes meeting audio locally on your machine, lets you jot quick memos during the call, and then generates a context-aware summary and chatable notes from the transcript plus your memos. No bot joins the meeting; the app listens to system audio and can run both speech-to-text and language models locally, or connect to models via your own API keys so data doesn’t have to leave your device hyprnote.com/product/local-ai, GitHub README.

Today it’s available as a macOS public beta distributed from their GitHub repo, with live transcript (including speaker identification), note templates, in-note AI chat, and integrations like Apple Calendar/Contacts and Obsidian. Cloud sync is optional and paid; the free tier supports bring-your-own keys and local models via tools like Ollama or LM Studio hyprnote.com/pricing, GitHub README, hyprnote.com/product/local-ai.

The project has an active open-source community and is a YC S25 company. Windows and Linux support, deeper third‑party integrations (e.g., Notion, Slack, HubSpot, Salesforce), and optional self‑hosted server components for team features and admin controls are on the roadmap, keeping a local‑first posture with enterprise controls for regulated customers Y Combinator profile, docs/roadmap, Hacker News discussion.

Who are their target customer(s)

• Privacy-sensitive regulated teams (legal, healthcare, finance): They can’t send meeting audio to third-party clouds and need to keep transcripts and models inside the company to satisfy compliance and reduce data exposure risk. Hyprnote’s local processing and planned self-hosted options address this need product/local-ai, docs/roadmap.
• IT and security administrators evaluating tools for rollout: They need admin controls, policy enforcement, and deployable options so employees don’t route sensitive audio or LLM calls through external services. Hyprnote is building team/server components and enterprise features for these requirements docs/roadmap, enterprise.
• Sales and support reps who join many calls: They spend time writing call notes and copying summaries into CRMs, often losing context and action items. Hyprnote’s summaries, action-item extraction, and planned CRM/Slack integrations reduce this manual work product/ai-notetaking.
• Product and engineering teams running frequent internal syncs: Decisions get lost across chat threads and shared drives, and switching apps mid-meeting hurts focus. Hyprnote’s live transcript, in-note chat, and upcoming Noteshelf/floating panel keep capture and follow-ups in one place GitHub README, docs/roadmap.
• Individual execs and consultants needing fast, private summaries: They have back-to-back meetings and want quick takeaways without sending sensitive audio to third-party clouds. Hyprnote runs local speech-to-text and LLMs for private summarization product/local-ai.

How would they acquire their first 10, 50, and 100 customers

• First 10: Convert engaged GitHub contributors and macOS beta users via concierge onboarding to configure local STT/LLMs, gather rapid feedback, and crystallize early case studies GitHub repo.
• First 50: Offer short self-hosted/on‑prem pilots to regulated teams and security evaluators via YC networks, HN, and targeted outreach, with migration help and documented controls proving audio stays local docs/roadmap, enterprise.
• First 100: Broaden reach with Windows/Linux betas and native CRM/Slack connectors; convert pilots with admin controls and self-hosted or managed options via MSP partners, supported by a procurement playbook (SLA, compliance docs, onboarding) GitHub README, pricing.

What is the rough total addressable market

Top-down context:

Vendors size the AI meeting assistant market at roughly $2.5–3.5B in 2024–2025, growing ~25%+ CAGR, while the broader speech‑to‑text API market is ~$4.4–5B in 2024–2025 Market Research Future, TBRC, Grand View Research, Allied MR.

Bottom-up calculation:

If Hyprnote targets 50,000 mid‑to‑large regulated and privacy‑sensitive organizations globally, landing an average of 100 seats per customer at $10/user/month, the directional TAM would be ~50,000 × 100 × $120 ≈ $600M annually. This captures the local‑first, self‑hosted segment of the broader market and excludes general cloud‑only notetakers.

Assumptions:

• Focus on regulated/privacy‑sensitive segments rather than the full AI meeting market.
• Average 100 paid seats per customer across pilots that convert to team deployments.
• ARPU of ~$10/user/month for team features and support.

Who are some of their notable competitors

• Otter.ai: Cloud-first AI meeting notes with calendared auto-join and a team workspace focused on collaboration and integrations; differs from Hyprnote’s local-first, on-device posture and planned self-hosting hyprnote.com/product/local-ai.
• Fireflies.ai: Cloud service that joins meetings to record, transcribe, and push notes into CRMs/analytics; optimized for company-wide conversation indexing, not local-only processing.
• Grain: Emphasizes recording, highlights, and shareable clips with syncing to team tools; centered on cloud storage/sharing rather than local-first privacy.
• Fathom: Lightweight meeting recorder for Zoom/Meet/Teams with instant summaries and CRM sync; built as a cloud-integrated recorder, not an on-device, self-hostable notetaker.
• MacWhisper (and similar Whisper-based apps): Local transcription apps for privacy-conscious users; strong for offline STT but typically lack Hyprnote’s meeting-centric UI, in-note chat, and upcoming team/self-hosted collaboration features.