TODO for AI
vs Lindy
No-code AI teammates for business workflows: email, CRM, meetings and support, built from triggers and steps. Here is where each one wins, with numbers, and who should pick which.
Most major models, you pick
Every providerWho should pick which
- Your work is repeatable, well-defined business processes
- You want a no-code visual builder rather than a prompt and a terminal
- The integrations you need are already in their catalogue
- You hand over goals, not pre-built workflows
- You want any CLI you install to be an integration, not only catalogue items
- You need a real shell on your PC, your cloud VM and your repo
- You want several vendors' models reviewing each other, and the cost in dollars
What Lindy is, and where it stops
Lindy is the most business-shaped tool on this list, and the one that best understands that most company work is a process. You assemble an AI teammate from a trigger and a set of steps, wire it into mail, calendar, CRM and the support desk, and it runs. You pick the model per task, computer use is included, and the integration catalogue is deep. For a workflow with a known shape, nothing here gets you live faster.
That shape is also the boundary. The unit of work is a workflow you designed, so open-ended requests have no step to hang on. Credits abstract away what a task really cost, and the conversion changes per plan. And because everything runs in Lindy's cloud, it never gets a shell on your machine, never touches a repo, and can only reach what the catalogue already covers.
Ops and go-to-market teams automating repeatable processes without writing code.
Three reasons Lindy users look elsewhere
Someone has to design the trigger and the steps before anything runs. An agent you can simply hand an unfamiliar goal to is a different product.
Integrations and computer use cover the SaaS side, but there is no shell on your PC, no cloud VM of your own and no repo, so your build, deploy and data tooling stays out of reach.
Costs land in credits, not dollars, and the rate differs by plan: 100 per dollar on Plus, about 175 on Max. Comparing what a task cost means converting first.
Six dimensions that decide it
What each one ships
Same ladder, different meter
Abstract credits: 100 per dollar at Plus, ~150 at Pro, ~175 at Max, so the same task costs different money on different plans. Top-ups are $10 per 1,000 and never expire.
One pool priced in dollars of model cost, spendable on any vendor. Session and weekly windows pace it, and a 1.3-1.5x plan multiplier applies, so a $20 plan is about $15 of list-price API. Team seat prices go into one shared pool.