Condens: UX research platform for storing, transcribing, tagging, and analyzing user interviews in a searchable, collaborative repository. joinly: Open-source, self-hostable connector that lets AI agents join Google Meet, Zoom, and Microsoft Teams calls to transcribe, listen, and act in real time via MCP. The right pick comes down to team size, budget, and the workflows you want to automate.
How Hosiqo compares and tests toolsFinal recommendation
Shortlist Condens when transcribing and tagging user interview recordings matters most, and joinly when self-hosted, privacy-first real-time meeting transcription for regulated teams matters most. Try them side by side on real calls before deciding — needs vary by team.
UX research platform for storing, transcribing, tagging, and analyzing user interviews in a searchable, collaborative repository.
Open-source, self-hostable connector that lets AI agents join Google Meet, Zoom, and Microsoft Teams calls to transcribe, listen, and act in real time via MCP.
Condens is a user research platform that helps research teams store, analyze, share, and scale customer data in one collaborative hub. It supports importing recordings, notes, and user feedback, and provides automated multilingual transcription with AI-powered speaker recognition and automated captions. For analysis, Condens offers a split-screen interface that lets researchers review raw data and tag it simultaneously, along with AI-driven pattern identification across datasets and quick generation of evidence-backed findings. All research lives in a searchable, centralized repository with cross-project insight discovery, filtering, and role-based access control for managing confidential data. Condens emphasizes real-time collaboration, allowing multiple team members to build, edit, and tag data together, and integrates with tools such as Slack, Teams, Figma, and Miro, plus whiteboard functionality for interactive sessions. Additional AI capabilities include automated bookmarking, summarization, and pattern detection across multiple studies. Positioned as a lean, practical tool for researchers who want to move quickly, Condens aims to streamline the path from interview transcripts to shareable insights without the overhead of heavier enterprise systems. Pricing varies by plan. Check the official website for current pricing.
Best suited for
joinly is an open-source middleware project (by joinly-ai) that makes meetings accessible to AI agents. It runs as a Model Context Protocol (MCP) server that equips any agent with the tools to join a live video call, capture a real-time transcript, and interact by voice or chat during the meeting. Rather than being a finished notetaker app, joinly is a framework developers use to build interactive meeting agents that can listen, answer, search the web, draft documents, and post chat messages while the meeting is in progress. It works cross-platform across Google Meet, Zoom, and Microsoft Teams (and browser-based calls), and is model-agnostic, supporting OpenAI, Anthropic, and local models through Ollama. Speech-to-text and text-to-speech are modular, with Whisper or Deepgram for transcription and Kokoro, ElevenLabs, or Deepgram for synthesis. The project is MIT licensed and deployed via Docker (with a separate CUDA GPU image), giving teams full data sovereignty. The MCP server exposes join/leave controls, transcript and participant access, audio control, chat messaging, and video snapshots, making it a building block for custom, privacy-first meeting automation. Pricing varies by plan. Check the official website for current pricing.
Best suited for
Condens is a free tier with paid upgrades (freemium); joinly is a free tier with paid upgrades (freemium). Always confirm current pricing on each vendor's site before buying.
| Feature | Condens | joinly |
|---|---|---|
| Core capability | Automated multilingual transcription with speaker recognition and captions | MCP server that exposes meeting tools (join/leave, transcript, chat, audio control, snapshots) to AI agents |
| Standout feature | Split-screen interface for simultaneous data review and tagging | Real-time transcription with timestamps and speaker information, subscribable for live updates |
| Team usage | AI-driven pattern identification across datasets | Cross-platform support for Google Meet, Zoom, Microsoft Teams, and browser-based calls |
| Integrations | Searchable centralized repository with cross-project discovery | Modular speech-to-text and text-to-speech backends (Whisper, Deepgram, Kokoro, ElevenLabs) |
| Languages & capture | Real-time collaborative analysis and tagging | Model-agnostic: works with OpenAI, Anthropic, and local LLMs via Ollama |
| Best-fit workflow | Integrations with Slack, Teams, Figma, and Miro plus whiteboards | Docker-based self-hosting with optional CUDA GPU image |
Condens
Choose Condens if you need transcribing and tagging user interview recordings — strengths include fast, practical workflow from transcript to tagged insights.
joinly
Choose joinly if you need building custom ai meeting agents that answer questions and run tasks during live calls — strengths include fully open source (mit) and self-hostable for complete data control.
Condens
joinly
It depends on your workflow. Condens is strong for transcribing and tagging user interview recordings, while joinly is strong for building custom ai meeting agents that answer questions and run tasks during live calls. Both transcribe and summarize meetings.
Condens is a free tier with paid upgrades and joinly is a free tier with paid upgrades. Check each vendor's pricing page for the latest plans and free-tier limits.
Sure. Running both makes sense when their strengths don't overlap and the budget allows.
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