How to migrate from Pipefy to Tallyfy

If you’re moving from Pipefy to Tallyfy, the short version is this: your card data comes across without much drama, and the real work is changing the shape of the process. Pipefy is a Kanban tool. You build a pipe, give it phases, and drag cards from one phase to the next. Tallyfy runs the same work as a single ordered sequence that moves on its own, with approvals that can genuinely stop a card from jumping ahead before it’s ready. That switch, from a board you push cards across to a process that holds its own order, is the entire job. It sits underneath most workflow software moves, and it pays to understand it before you export a single pipe.

Why teams move off Pipefy

Credit where it’s due first. Pipefy does Kanban-style process management well, and finance and procurement teams in particular have run serious volume through it for years. If your work fits a board with phases, it’s a capable tool, and a migration guide that pretends otherwise isn’t honest.

The pressure builds when the board stops matching the work.

A Pipefy phase is a column. A card sits in it until someone drags it onward, and nothing about that column insists the work was actually done. Cards land in an “Approved” phase without anyone approving anything, because moving the card is the approval. For a small team watching its own board, that’s fine. For a process that has to run the same way every time, with sign-offs that can’t be skipped, the looseness becomes the problem.

So what pulls teams toward Tallyfy?

Usually it’s direction. They want a process that enforces its own order rather than trusting where a card sits, an AI-native foundation instead of automations bolted onto a board, and a pricing and ownership fit that holds up as they grow. The difference between BPM and plain workflow is worth reading on that point, because Pipefy sells itself as BPM while running like a task board, and the gap between those two is exactly what teams feel when they outgrow it.

What Pipefy export actually gives you

Start with the export, because it sets the plan. Pipefy is API-first: its GraphQL API reads your pipes, cards, and phases programmatically, which is the complete machine-readable path if you want to pull everything out cleanly. For a lighter touch, you can export a pipe report as a spreadsheet straight from the interface, emailed to you and ready to open in Excel, Google Sheets, or a BI tool.

There’s one limit worth knowing before you rely on it. A Pipefy report only exports the first 30,000 lines, so if a pipe holds more cards than that, the spreadsheet quietly stops at the cap. For most single pipes that’s plenty, but a high-volume pipe needs the API route instead.

Turns out the catch that actually shapes the timeline isn’t the card data.

Pipefy database tables are a separate, harder export. Tables are Pipefy’s relational store, the place teams keep vendors, contracts, products, anything a card looks up. They don’t come out the same way cards do, and Tallyfy has nothing that maps to them directly. If your pipes lean on database tables, that’s the painful part of the migration that needs real thought, not the card export. We’ll come back to it, because it’s the single most important thing to scope before you start.

How Pipefy concepts map to Tallyfy

This is the reassuring part, because the Tallyfy team keeps an explicit object mapping for Pipefy, and the pipe-level concepts line up cleanly. The card-level data is easy. Phases are where the rethink lives.

The defining shift is Kanban to sequential, and it deserves a slow look. In Pipefy, a phase is a column, and you drag a card into it and out the far side. In Tallyfy, that same phase becomes a short run of three steps: an entry where the card arrives, the work itself, and an exit that checks it’s done before the next phase begins. That exit is usually an approval that blocks the next step, the thing a Kanban column never had, so the process can refuse to advance instead of hoping nobody dragged a card too soon.

Picture an accounts-payable pipe, since that’s classic Pipefy territory. You’ve got phases for invoice received, coding and matching, manager approval, and scheduled for payment, and each invoice is a card you drag rightward as it clears each stage. Rebuild it in Tallyfy and the pipe becomes one accounts-payable blueprint.

Invoice received becomes the kickoff that captures the invoice details. Coding and matching becomes a work step. The manager-approval phase, which on the board was just a column you trusted, becomes a real sign-off that the invoice can’t pass until it’s granted. Scheduled for payment becomes the final step. Same flow, but now the process insists on the approval rather than reading meaning into where a card happens to sit.

The field types come across cleanly too. Short and long text, number, and date map straight over, currency becomes a number, a connection field becomes a stored reference, a statement becomes read-only instruction text, and a formula field arrives as a static value because the calculation is documented rather than run. One honest cost of the shape change: a pipe with five phases doesn’t become five steps. It basically lands closer to fifteen, because each phase expands into its entry, work, and exit. The data is small. The rethink is the work.

A realistic migration timeline

A handful of simple pipes with no database tables can genuinely move in two to three weeks. A finance team running table-heavy pipes with deep automation should plan for considerably longer, and the database tables are why.

Week one is export and audit, and the audit matters more than the export. Pull your pipes and ask one question of each: is this a real recurring process, or a board someone set up once and never reused? The recurring ones, the AP flow, the procurement intake, the onboarding pipe, are your candidates. While you’re there, list every pipe that depends on a database table, because that list decides how long this takes.

Week two is the rebuild. Recreate your top two or three pipes as Tallyfy blueprints, turning each phase into its entry, work, and exit steps and deciding which exits are real approvals. This is also where automations get rebuilt as conditional rules, which is the same IF-THEN logic expressed differently, so it needs recreating and testing rather than copying.

Week three onward is the database-table question and the parallel run. For pipes that lean on tables, decide where that data lives now, an external database the process references, or a rethink of whether it needed to be relational at all. Then run one team on Tallyfy beside Pipefy, confirm the rules behave, and switch over once they do.

Why not just rebuild the phases one for one and call it finished?

Because the phases were never the process. They were columns to park cards in. Turning them into a sequence with real gates is the reason you’re moving, and a database-driven pipe that fights that shape is exactly the one to question before you commit to it.

What breaks, and what Tallyfy won’t replace

Let me name the things that don’t carry. Automations get rebuilt as rules, not imported. Phase-specific forms collapse into the steps that need them. Card-cloning with updates and public-portal features don’t transfer. And the visual Kanban order, the left-to-right position that some teams read as priority, means nothing after the conversion, so anything it carried has to become an actual field.

Now the part to weigh carefully, because it’s the reason some Pipefy setups shouldn’t migrate wholesale at all.

Database tables. They’re Pipefy’s relational data store, and Tallyfy has no direct match, so that data needs an external home and a way to feed it into your processes. The Tallyfy team’s own mapping is blunt about this: a table-heavy pipe can multiply the migration effort many times over, because you’re not just rebuilding a process, you’re standing up a separate, messy data layer beside it. If your pipes are really database applications with a workflow attached, be honest with yourself about that before you start. One thing that catches teams off guard, though, is how little they miss the Kanban board itself once the process runs on its own. The board felt essential right up until a single live view of every running process replaced it, and then it didn’t.

Built AI-native, with the process enforcing its own order instead of a board.

The shift teams settle into fastest is reading process by status instead of by board geometry. On a Pipefy board you scan columns to guess where things stand. In Tallyfy every run of the process sits on a named step, so instead of counting cards in a column you just see which two are stuck and where. If you’re weighing the move against keeping a board, the honest comparison is less about features and more about whether a board can run a process, which is exactly what Kanban boards versus structured views digs into.

Common questions about migrating from Pipefy

If you’re still weighing the decision rather than ready to move, our Pipefy alternative comparison covers why teams switch, feature by feature. This guide is the hands-on half of that pair.

When you’re ready to plan the move itself, the most useful first step is a short call where we look at your busiest pipes, confirm how cleanly they map, and flag whether any database tables are going to need their own plan.

Book a 30-minute migration walkthrough and bring the two or three pipes your team runs most. That’s the surest way to tell whether it’s a fit.