Who maintains the integrations when an API changes?

That’s the main catch, so we price maintenance up front along with the build. Either your team takes it on or we do, whichever you prefer. Rarely used integrations are better left on Zapier, where the vendor maintains them.

What does the move cost?

The build is $30k–$80k and running it costs $2k–$8k a year. If the platform costs you $12k–$65k a year, it pays back in 8–18 months.

What about AI steps like classification or parsing emails?

In your own code the model is called directly and you pay only for its work. In Make the same steps burn credits that vary with tokens, on top of the platform fee.

Category 2 of 7

Replace Zapier and Make with your own code: no per-task fees

We find the workflows that consume most of your task budget and move them into your own code: a scheduled worker on a small server or a serverless function. Everything else keeps running on Zapier, where the convenience is worth paying for.

≈$1,462 → $40–$150 a month at 100,000 tasks
Pays back in 8–18 months
Your team keeps the Zapier it knows

Tools you may be paying for now

Zapier
Make
Workato
Tray.ai
Celigo
Boomi

100,000 tasks a month

≈$1,462 / mo$40–$150 / mo

Zapier Professional versus the same logic running as a scheduled worker on a small server or a serverless function. The work itself is HTTP calls and data mapping, and its compute cost is close to zero.

Why you are overpaying

Integration plumbing: Zapier, Make, Workato, Tray, Celigo, Boomi.

Vendors here use four different billing units, and the totals drift far apart at higher volume. Zapier bills per task, meaning per action step, so a five-step automation uses five tasks every time it triggers. Make bills per credit, and for AI steps the credit count scales with tokens, file size or processing time. Workato and Tray bill per job on negotiated contracts. Celigo and Boomi bill per endpoint, which stays flat however much volume you run.

Keep the tool, move the volume

Zapier and Make are very good for working out what an automation should do and expensive for running it at volume, because the thing they meter (an HTTP request and a field mapping) costs almost nothing. So we leave Zapier in place. We move the ten or so workflows that eat 80% of your task budget into your own code and keep the long tail on Zapier, where its convenience is worth paying for.

AI changes this category in two ways. Models now write the integration code, so moving a workflow costs far less than it used to. And steps that need judgement, classification or unstructured input can now be automated. In Make those steps burn token-metered credits on top of the platform fee, while your own code calls the model directly with no platform fee.

What we build

The high-volume workflows that consume most of your task budget, as your own code
Steps that need judgement or classification, without token-metered credits on top of a platform fee

What stays as is

The long tail of workflows on Zapier or Make, so your team keeps the tool it likes
Rarely used connectors: keeping up with other companies’ API changes is an ongoing obligation rather than an asset

Where Zapier earns its money

What Zapier really sells is its connector library: thousands of maintained integrations that quietly absorb every upstream API change. Rebuilding twelve integrations takes a weekend. Keeping them working through four years of API deprecations is a job that never ends. That is why we price the maintenance along with the build, so the code stays an asset for you instead of turning into a liability.

Build economics

Build$30k–$80k

Annual run cost$2k–$8k

Displaced annual spend$12k–$65k

Break-even8–18 mo

Indicative ranges for a production system rather than a prototype: authentication, audit log, error handling, monitoring and a usable admin are included. Build assumes AI-assisted delivery by a senior team. Run cost covers inference, hosting, monitoring and maintenance, but not new features.

How the project goes

01
SaaS audit
Identify which tools have the highest cost-to-utility ratio.
02
The 80/20 parity
Instead of aiming for 100% feature parity, build the 20% of features your team uses 80% of the time.
03
Context-first architecture
Design the system around your data (vector databases + RAG) so the AI understands your jargon, clients, and history from day one, and organize it around workflows rather than apps.
04
An AI-native operating model
Plan governance, risk controls, human oversight, data readiness, and team structure as part of the strategy instead of leaving them for cleanup after launch.
05
Phased decommissioning
Run the custom tool in parallel with the SaaS for 30 days before cutting the subscription.

Cases

PlaceholderA case for this category is on its way

Here goes a project in this category: the task, what we built and the before/after figures.

PlaceholderA case for this category is on its way

Here goes a project in this category: the task, what we built and the before/after figures.

Questions about this replacement

No. We move only the high-volume workflows, usually the ten or so that eat 80% of the task budget. The long tail stays on Zapier or Make.

Let’s size this for your company

Tell us which tool you pay for and roughly what volumes you handle. We’ll come back with an honest estimate and tell you if switching to another vendor makes more sense than building.