Aspect: AI interview assistant that records, transcribes, and summarizes recruiting interviews, then autofills ATS scorecards. Minutes: Open-source, local-first conversation memory layer that records and transcribes meetings, diarizes speakers, and stores searchable notes as markdown for AI agents. Which one wins depends on your platform mix, budget, and how hands-off you want notes to be.
How Hosiqo compares and tests toolsFinal recommendation
Shortlist Aspect when capturing and summarizing candidate interviews automatically matters most, and Minutes when recording and transcribing calls locally for users who refuse cloud meeting tools matters most. Run both through a week of actual calls to see which suits your workflow.
AI interview assistant that records, transcribes, and summarizes recruiting interviews, then autofills ATS scorecards.
Open-source, local-first conversation memory layer that records and transcribes meetings, diarizes speakers, and stores searchable notes as markdown for AI agents.
Aspect is an AI interview assistant built for recruiters and hiring teams that joins interviews on Zoom, Google Meet, and Microsoft Teams to record, transcribe, highlight, and summarize candidate conversations. Instead of taking manual notes, interviewers can stay focused on the conversation while Aspect captures everything said and generates structured AI interview notes and summaries afterward. A central feature is its scorecard autofill, which uses the captured interview data to populate candidate evaluation forms with a single click and syncs notes and summaries back into the applicant tracking system. Aspect integrates with common ATS platforms such as Greenhouse, Lever, and Teamtailor so interview records flow directly into existing hiring workflows. The platform also provides interview analytics and AI coaching feedback intended to help interview teams improve consistency and reduce subjective bias over time. By standardizing how interviews are documented and evaluated, Aspect aims to make hiring decisions faster and more data-driven. It offers a free tier for a limited number of interviews alongside paid plans for teams. Pricing varies by plan. Check the official website for current pricing.
Best suited for
Minutes, built by Mat Silverstein, is an open-source, privacy-first conversation memory layer that captures meetings, calls, voice memos, and dictation and turns them into searchable, AI-accessible notes. It transcribes audio locally using whisper.cpp or Parakeet so audio never has to leave the machine, performs speaker diarization to separate voices, and extracts decisions and action items, writing everything to the user's own disk as plain markdown files with structured YAML frontmatter. Because the output lives in a local folder (for example ~/meetings/), the notes can sync across devices through iCloud, Dropbox, or Google Drive and can be read directly by AI tools. A central design goal is integration with AI assistants: Minutes runs an MCP server exposing a large set of tools so coding and chat agents such as Claude, Codex, Gemini CLI, and others can query past conversations, track relationships across meetings, and surface what was promised to whom. It ships as a macOS desktop app with a menu-bar recorder and AI assistant, plus a cross-platform command-line interface, and includes a dictation hotkey mode. The project is MIT licensed, installable via Homebrew, and actively maintained with frequent releases, making it a fully self-hostable option for people who want durable, private, searchable meeting memory rather than a cloud subscription. Pricing varies by plan. Check the official website for current pricing.
Best suited for
Aspect is a free tier with paid upgrades (freemium); Minutes is a free tier with paid upgrades (freemium). Always confirm current pricing on each vendor's site before buying.
| Feature | Aspect | Minutes |
|---|---|---|
| Core capability | Records, transcribes, highlights, and summarizes interviews across Zoom, Google Meet, and Microsoft Teams | Local transcription with whisper.cpp or Parakeet, no cloud audio upload |
| Standout feature | AI-generated interview notes and candidate summaries | Speaker diarization to attribute who said what |
| Team usage | One-click scorecard autofill from captured interview data | Plain-markdown output with YAML frontmatter stored on your own disk |
| Integrations | ATS integrations including Greenhouse, Lever, and Teamtailor | MCP server exposing tools so AI agents can query meeting history |
| Languages & capture | Interview analytics and team performance visibility | Cross-meeting search, relationship tracking, and action-item extraction |
| Best-fit workflow | AI coaching feedback for interviewers | macOS desktop app plus cross-platform CLI and dictation hotkey mode |
Aspect
Choose Aspect if you need capturing and summarizing candidate interviews automatically — strengths include reduces manual note-taking so interviewers can focus on candidates.
Minutes
Choose Minutes if you need building a private, searchable memory of meetings and voice notes that ai agents can query — strengths include fully local-first and mit licensed, keeping conversation data private and portable.
Aspect
Minutes
It depends on your workflow. Aspect is strong for capturing and summarizing candidate interviews automatically, while Minutes is strong for building a private, searchable memory of meetings and voice notes that ai agents can query. Both transcribe and summarize meetings.
Aspect is a free tier with paid upgrades and Minutes is a free tier with paid upgrades. Check each vendor's pricing page for the latest plans and free-tier limits.
Often yes: teams combine tools when one handles capture and another handles analysis.
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