CallFinder: CallFinder is an AI-powered speech analytics platform that transcribes and analyzes contact center calls to automate quality assurance and surface customer insights. Scriberr: Open-source, self-hosted AI audio transcription app that runs Whisper models locally with speaker diarization, summaries, and chat-with-transcript. Here's where each one pulls ahead on pricing, features, and the meetings it suits best.
How Hosiqo compares and tests toolsFinal recommendation
Shortlist CallFinder when automating quality assurance and call scoring in contact centers matters most, and Scriberr when researchers and journalists generating diarized transcripts of recorded conversations matters most. Trial each on a few real meetings before you commit — the better fit usually shows fast.
CallFinder is an AI-powered speech analytics platform that transcribes and analyzes contact center calls to automate quality assurance and surface customer insights.
Open-source, self-hosted AI audio transcription app that runs Whisper models locally with speaker diarization, summaries, and chat-with-transcript.
CallFinder is a cloud-based speech analytics and conversation intelligence platform built for contact centers and quality assurance teams. It captures audio by integrating with a company's existing call recording provider and contact center systems, then applies AI-powered speech-to-text to produce searchable transcriptions of agent-customer interactions. Beyond transcription, the platform delivers automated agent scorecards, sentiment and emotion analysis (positive, negative, or neutral), and silence and overtalk detection to pinpoint conversation patterns and customer pain points. Custom analytics reporting helps managers identify trends, compliance risks, and coaching opportunities across large call volumes. A distinguishing element is its managed client services model, in which an assigned Speech Analyst works alongside the QA team to define goals and optimize the deployment, combining AI with human review. CallFinder integrates with most CRMs and contact center solutions, with a typical implementation taking several weeks. It is aimed at contact centers in industries such as credit unions, healthcare, collections, insurance, and education seeking to monitor and improve customer interactions.
Best suited for
Scriberr is an open-source, self-hosted audio transcription application aimed at people who want to keep recordings and transcripts on their own hardware. It uses the open-source Whisper family of models (via the WhisperX engine) to transcribe audio and video files entirely offline, with no requirement to send data to a cloud provider. The project is distributed under the MIT license and is packaged as a single binary, with a Go backend and a Svelte frontend compiled into the binary, while Python handles the underlying AI transcription. Beyond raw transcription, Scriberr can automatically detect and label different speakers (diarization), generate summaries using custom prompts, and let users chat with a transcript by connecting to Ollama or OpenAI-compatible providers. It includes a transcript reader with playback follow-along and seek-from-text, a built-in audio recorder, note-taking, and a folder watcher plus API endpoints for automation and integration with tools like n8n. The maintainer publicly noted development is paused but not abandoned, and community contributions are welcome; the most recent release at the time of review was v1.2.0 in December 2025. Pricing varies by plan. Check the official website for current pricing.
Best suited for
CallFinder is custom pricing (contact sales); Scriberr is a free tier with paid upgrades (freemium). Always confirm current pricing on each vendor's site before buying.
| Feature | CallFinder | Scriberr |
|---|---|---|
| Core capability | AI-powered speech-to-text call transcription | Local, offline transcription using Whisper models via the WhisperX engine |
| Standout feature | Searchable transcripts of agent-customer interactions | Automatic speaker diarization (who said what) |
| Team usage | Sentiment and emotion analysis | AI summaries with custom prompts via Ollama or OpenAI-compatible providers |
| Integrations | Automated agent scorecards | Chat with your transcripts to ask questions and pull insights |
| Languages & capture | Silence and overtalk detection | Built-in audio recorder and note-taking on transcripts |
| Best-fit workflow | Custom analytics and reporting | Folder watcher and API endpoints for automation workflows |
CallFinder
Choose CallFinder if you need automating quality assurance and call scoring in contact centers — strengths include combines ai analysis with a dedicated human speech analyst.
Scriberr
Choose Scriberr if you need privacy-conscious teams transcribing meeting and interview recordings on their own infrastructure — strengths include fully self-hosted and offline, keeping audio and transcripts on your own hardware.
CallFinder
Scriberr
It depends on your workflow. CallFinder is strong for automating quality assurance and call scoring in contact centers, while Scriberr is strong for privacy-conscious teams transcribing meeting and interview recordings on their own infrastructure. Both transcribe and summarize meetings.
CallFinder is custom pricing and Scriberr 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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