Assistly vs CleanSlop: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Assistly and CleanSlop — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Assistly

Freemium

A live meeting assistant for Mac and Windows that reads call audio locally and shows guidance in an overlay excluded from screen shares.

Bot-Free System Audio Capture: Works from your computer's audio rather than joining the meeting, so nothing appears in the participant list and there is nothing to integrate with the call app.
Screen-Capture-Excluded Overlay: The assistant window is excluded from screen capture at the OS level, so it stays visible to you and invisible in shares and recordings.
Auto-Assist Without Prompting: Detects when a question lands or when you think out loud and streams structured talking points into your thread automatically, with no hotkey and no break in eye contact.
Multi-Speaker Language Tracking: Separates your voice from other participants and follows who said what across dozens of auto-detected languages, even when the call switches language mid-sentence.
Two-Way MCP Context: Pulls context from Google Calendar, Notion, Linear or any MCP server during the call, and exposes your meeting history back over MCP so Claude, ChatGPT or Cursor can query it later.
Personas from Your Material: Builds a persona from your CV, docs and notes and switches modes for a sales call, client review or interview so responses match your background and phrasing.
Automatic Recap and Action Items: Turns the transcript into a summary with owners and deadlines the moment the call ends, auto-saved and searchable across sessions.
Per-Client Projects: Files each session to a project based on the calendar, and scopes answers and mid-call lookups to that client's history so context never crosses between accounts.

Live Sales Calls: Surfacing objection handling and product detail the instant a prospect asks, without breaking eye contact to search a doc.
Client Account Reviews: Recalling what was committed to a specific client in a previous session, with the source call cited, while the review is still running.
Non-Native Language Meetings: Following a call that switches language mid-sentence and receiving guidance in clear English.
Customer Success Handoffs: Leaving every call with a written summary and assigned action items instead of reconstructing notes afterwards.
Meetings Where Bots Are Unwelcome: Getting live assistance on calls with clients or legal teams who object to a recording bot joining the room.
Querying Past Meetings from Your Editor: Asking Claude, ChatGPT or Cursor what was agreed in a past session over MCP without opening the app.

Freemium

Scans vibe-coded apps for launch-blocking issues like leaked keys and data exposure, and reports what to fix first, right from your coding agent.

Agent-Native Scanning: Tell Claude Code, Codex, Cursor or other agents to scan with CleanSlop and fix findings where you build.
System-Level Code Mapping: Maps routes, background jobs, data and external services so each finding follows a real call path.
Prioritized Reports: Findings grouped as needs attention, worth a look and minor, worst first.
Evidence for Every Finding: Shows where each issue lives in your code and why it was flagged.
Plain-English Fixes: Explains what is wrong, why it matters and what to do about it.
Copy for LLM: Hands any report to your AI tool so it can apply the fixes.
GitHub App Integration: Scan only the repositories you select, read-only access.
Expert Triage Calls: Book a 15-minute call with a CleanSlop engineer to walk through findings.

A solo founder checks a Next.js and Supabase app built with an AI coding assistant before launching.
A developer discovers an exposed AI API key bundled into browser code and moves it to a server route.
A side-project builder verifies that one user's data cannot be read by another through database policies.
A Claude Code user runs a scan from the terminal and has the agent fix the top findings.
A team lead gets a short prioritized list instead of hundreds of linter warnings.
An indie hacker books an expert triage call to confirm an ambiguous finding.