Slashy vs Taste Lab: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Slashy and Taste Lab — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Slashy
Slashy
Slashy is an AI-native email client that drafts replies in your voice, triages what matters, and makes sure no follow-up slips through.
Key features
- AI Reply Drafting: Drafts email replies in your own voice so you can review and send in seconds.
- Smart Triage: Automatically surfaces the emails that matter and filters out inbox noise.
- Follow-up Tracking: Tracks pending conversations so no follow-up slips through the cracks.
- AI-Native Inbox: A redesigned email client built around AI rather than added onto an old one.
- Enterprise Controls: SSO, SCIM, and customized security controls for teams on the Enterprise plan.
Best for
- Clearing a Busy Inbox: Triage and respond to high volumes of email in a fraction of the usual time.
- Consistent Voice Replies: Draft on-brand responses that sound like you without writing from scratch.
- Never Missing Follow-ups: Stay on top of threads that need a reply or a nudge.
- Team Email at Scale: Roll out an AI email client across an organization with SSO and SCIM.
Taste Lab
Sen Lin
Taste Lab is a Claude Code skill that turns any URL into a complete design context: design tokens plus the reasoning and trade-offs behind every choice.
Key features
- Design Map Extraction: Captures every color, font weight, spacing value, radius, and shadow with exact px/hex/ratio citations across 20 measurement categories.
- Taste DNA Inference: Derives four design principles, each with a Trigger, Decision, Reason, Evidence, and Trade-off explaining why each choice was made.
- Four-Agent Pipeline: Runs Extract, Detect Patterns, Infer Taste, and Observer stages, each reading the page through a sharper lens.
- Anti-Slop Quality Gate: A final critic stage runs anti-slop checks and validates JSON before writing output.
- Dual File Output: Writes a {domain}.md and {domain}.json that any AI agent can build from.
Best for
- Cloning Design Systems: Give an AI agent a complete, reasoned design context to rebuild a site's look and feel.
- Design Reviews: Understand the deliberate trade-offs behind a website's visual decisions.
- Agent-Assisted Frontend Work: Feed structured taste files into coding agents so they make the right call on unseen pages.