# Build brief — a focused alternative to Fathom > **Verdict:** Partly, if you narrow it · **Buildability:** 57/100 · **Category:** Meeting Notes > **Source:** https://www.canitbevibecoded.com/fathom-ai > Independent editorial assessment from Can It Be Vibe Coded? Not affiliated with, endorsed by, or derived from Fathom. Verify current pricing and capabilities before acting. ## Context **Fathom** — AI meeting recorder that summarizes calls and syncs notes to tools. It currently costs $20/mo. A solo clone can handle recordings, transcripts, and summaries, but the product's paid value is automated capture plus CRM/workflow sync and team sharing. This brief describes a focused, single-operator replacement for the part of Fathom that is genuinely reproducible. It is deliberately narrower than the product it replaces, and it says so in writing. Build the useful core; do not pretend to have rebuilt the rest. ## What you are building Record or import calls, transcribe, summarize by template, clip moments, and push notes to a CRM or docs destination. - Capture supplied audio, transcribe it, create structured notes, and export them. - A responsive interface with real empty, loading, success, and error states. ## Requirements ### Functional - Calendar/Zoom/Meet/Teams integration. - Hosted database. ### Data and integrations - Speech-to-text API. - LLM API. - Optional CRM API keys. Each of these needs a real account, credential, or quota. Set them up before writing feature code. ### Non-functional - Accessibility: semantic markup, labelled controls, visible focus, and reduced-motion support. - Security: server-side secrets, validated input, and no credentials in the client bundle. - Reliability: retries with backoff on external calls, and a clear failure state when a provider is down. - Portability: the operator can export their data and leave without losing it. ## Implementation brief Build me a personal call-notes pipeline to replace Fathom. Requirements: - A watched folder: I drop call recordings (m4a/mp3/mp4) into ~/Calls/inbox/, chokidar picks them up, a Node pipeline processes each one. - Transcribe with whisperX for speaker-labeled, timestamped transcripts, or a hosted Whisper API if a key is present in .env. - Summarize with an LLM (key in .env) using templates in ./templates/*.md. The default produces a 5-bullet summary, decisions, action items with owners, and open questions. Pick the template from the filename prefix (sales-, 1on1-). - Clips: any transcript line can be cut into a share-able moment, ffmpeg trims 15 seconds either side of the timestamp into ~/Calls/clips/. - Output per call: ~/Calls/notes/YYYY-MM-DD-.md, summary on top, full transcript below a divider. - A small local web page (Express, localhost) listing calls with keyword search over transcripts. - No accounts, no telemetry; audio never leaves my machine unless I opt into the hosted API. - Out of scope: a bot that joins meetings, calendar auto-capture, CRM sync, team libraries. I record with my meeting app or OS and drop the file in. - README: dependencies, keys, and how to capture system audio on macOS. ## Delivery standard - Inspect the repository first, then write a short implementation plan before writing code. - Deliver the smallest complete end-to-end workflow first; every primary control must work against persisted data. - Use real validation and storage; never substitute fake dashboards, decorative controls, hard-coded success states, or mock integrations. - Include responsive layouts plus genuine empty, loading, success, validation, and failure states. - Keep secrets server-side in environment variables, provide .env.example, and never commit credentials or user data. - Add structured logs around every external call and return actionable errors without leaking sensitive details. - Write unit tests for the core logic and one automated test of the main user journey. - Finish with a README covering setup, architecture, data location, backups, tests, deployment, and known limitations. ## Acceptance criteria - [ ] A clean install starts the app using only the README and .env.example. - [ ] The primary journey works from first visit through saved result, reload, edit, export, and deletion where applicable. - [ ] Invalid input, missing configuration, provider failure, and an empty database each have a usable state. - [ ] The interface works at 390px and 1440px, is keyboard navigable, and shows visible focus on every control. - [ ] Tests, type checking, linting, and a production build all pass with no ignored failures. - [ ] No part of the interface implies a live integration, security guarantee, or scale capability that was not actually built and verified. ## Non-goals Do not build these, and do not claim to have replaced them: - Automatic call capture. - Integrations. - Searchable team library. - Polished clips. - Connectors, OAuth flows, and vendor API changes require constant upkeep. - Permissions, presence, and shared workflows are difficult to simplify. ## What you still own after launch - Secure credentials, rotate secrets, and handle provider rate limits. - Run migrations, backups, restores, and dependency updates. - Test the critical journey after every model, API, or hosting change. - Monitor failures and fix the edge cases a first prompt will miss. - Maintain every third-party integration as APIs and OAuth rules change. ## Risk **Operational risk.** The code is achievable; dependable data, integrations, and ongoing operations are the real cost. Editorial confidence in this assessment: high. No independent one-shot implementation is linked yet. ## Prior art Working open-source software you can read, fork, or borrow from before starting: - [whisperX](https://github.com/m-bain/whisperX) — Useful for transcript alignment and speaker-labeled call records --- Generated by [Can It Be Vibe Coded?](https://www.canitbevibecoded.com) · Full report: https://www.canitbevibecoded.com/fathom-ai