TaskyTrack turns client calls into PRDs and build-ready specs for AI coding tools. Free plan, paid plans from $20/month. See features and pricing.
Researched and fact-checked by Bartu Cavusoglu · Updated October 26, 2026
TaskyTrack is an AI product specification tool for people who turn client conversations into software. It reads a discovery call and drafts a structured spec: the project type, feature-by-feature requirements, a data schema, a UI direction, and a list of assumptions and open questions. The goal is to replace the manual work of turning messy meeting notes into a brief a developer can build from.
The product is aimed at agencies, freelance developers and designers, and in-house product and sales teams. It works as an AI PRD generator that writes from the client's own words rather than from a one-line idea. The company also describes the output as covering the core of a software requirements specification, meaning functional requirements and the data model, without the formality of an IEEE-style document.
The workflow has three steps. You first capture the call by pasting a transcript, giving a meeting link to the note-taker, or connecting a calendar so the note-taker joins the meetings you choose. TaskyTrack then reads the conversation and drafts the spec, grounded in what the client actually said, with each part traceable to the discussion.
In the last step you review and edit anything, then hand the spec off. You can download spec.md, copy it as a prompt for an AI coding tool, or scaffold a starter GitHub repo. Before a transcript reaches the third-party AI model, client names, email addresses and phone numbers are removed, and the content is processed through a paid API that does not train on it.
The spec itself is the core feature. Requirements are written page by page as mini build-briefs, using the client's stated priorities. The data schema lists tables, fields and relationships the product needs, and stays empty when no database is required. The UI direction captures the colors, mood and aesthetic the client asked for as a starting theme.
Two other features set it apart from a plain summary. Assumptions and open questions are listed explicitly, so gaps are visible before kickoff instead of mid-build. Every part of the spec is editable, and nothing is final until the user approves it. Capture options include pasted transcripts, a note-taker for meeting links, and read-only Google Calendar integration.
TaskyTrack is an AI tool that turns client discovery calls into build-ready product specs. The spec includes project type, feature-by-feature requirements, a data schema, a UI direction, and assumptions and open questions. Users review it and then export it to their build tools.
TaskyTrack has a Free plan at $0, Pro at $20 a month and Max at $100 a month, billed monthly in USD. Free includes 3 specs a month, Pro includes 30, and Max is unlimited. You can cancel anytime.
Yes. The Free plan includes 3 specs a month, meetings up to 15 minutes, manual paste and send-a-bot capture, and spec.md and copy-as-prompt export. No card is required to sign up.
No. You can paste a transcript you already have, give a meeting link to the note-taker, or connect your calendar so the note-taker joins meetings you choose.
It works with any tool that accepts a text prompt or reads repo files, including Cursor, v0, Bolt.new, Lovable, Claude Code and Windsurf. It exports a prompt, a spec.md file or a starter GitHub repo. It is an export, not a native plugin.
Those notetakers produce transcripts, summaries and action items. TaskyTrack produces a build-ready spec with requirements, a data schema, a UI direction and open questions. You can paste a transcript from one of them into TaskyTrack.
TaskyTrack requests read-only calendar access and never modifies events. Client names, emails and phone numbers are removed before a transcript is sent to the AI, which processes content through a paid API without using it for training. The company says it does not sell or share data.
Not natively. The spec downloads as plain Markdown, so you can paste it into a Linear or Notion document and create tickets from the feature breakdown.