Lindy

Lindy builds AI agents for routine business work across marketing, sales, support, operations, finance, product and engineering. Its published use cases are deliberately specific: tracking competitors, triaging a support queue, building a meeting deck, analysing a funnel, comparing vendors, logging invoices, updating a CRM, building dashboards, monitoring ad spend, chasing month end and filing engineering tickets.

Naming concrete tasks rather than describing a capability is the smartest thing about how this is sold. Most agent platforms ask a buyer to imagine what they might automate, which is a research project the buyer does not have time for. A list of jobs someone recognises from their own week converts far better, because the evaluation becomes whether this one thing works rather than whether agents are useful in general.

Pricing per user with a credit allowance rather than purely on consumption suits that positioning. A support lead evaluating queue triage needs a predictable monthly figure to get approval, and pure consumption pricing makes that impossible to forecast before deployment.

A Chrome extension alongside the platform reflects that much of this work happens in a browser tab rather than in a workflow tool, which is where automation usually fails to reach.