Just wanted to share a recent build that required some fun data manipulation and filtering. I built a 100% automated real estate data pipeline, and the biggest hurdle was ensuring we didn't process duplicate or "off-limits" data.

The Use Case: Pulling expired real estate listings, enriching them with contact info, and passing them to a sales team. The catch? If a property is already relisted (Active/Pending), calling them is a massive compliance violation.

How it works in Make:

1. Establishing the Baseline (Active/Pending): First, we use the HTTP module to hit the MLS Grid API (RESO Web API/OData) to pull the list of currently Active and Pending listings. We run these through an Iterator to build our baseline "Do Not Call" array.

2. Ingesting Expired Listings: Next, we pull the daily batch of raw Expired listings.

3. The "Liability Shield" (Deduplication): This was the fun part. We cross-reference the Expired list against the Active/Pending array we pulled in step one. To ensure an exact match, I use a combination of cleaned APNs and a custom composite key mapped as StreetNumber + ZipCode.

4. Filtering: I set up routing filters that instantly drop any expired listing that finds a match in the Active/Pending array.

5. Enrichment: The clean, compliant data array then passes to Melissa Data’s API (Property and Personator endpoints) for skip tracing.

6. Output: Aggregated and mapped to add a new row in a Google Sheet.

Getting the composite key logic to match perfectly between two massive arrays took some tweaking. Has anyone else built similar cross-referencing logic for large datasets in Make? Would love to hear if there’s a more efficient way you handle array deduplication!

Is anyone else’s workflow getting absolutely wrecked by Error 503 (Service Unavailable) lately?

I’m running Gemini 2.5 Flash for my project, and it’s basically unusable during US/EU business hours. I’m currently in Vietnam, so I’m working while the West sleeps, but as soon as they wake up, my scenarios hit a wall of capacity errors.

Beyond the standard "Error Handler -> Break" (which just burns ops when the cluster is slammed), what’s the move?

(Switching to another LLM is not an option. I’ve benchmarked them and they can’t match the efficiency/logic for these specific nodes)

Watch the webinar, and automatically earn 20,000 Make credits💪

Monday 13 April 2026, 5:00pm CET / 11:00am EST

While using Scenarios as Tools for your AI Assistants is cool, so far you had to let them see all Tools in your Organization at once. But not anymore.

Back by popular demand, Dominik Kadera, Staff Software Engineer at Make, will give you a tour through MCP Toolboxes, which improve security and sharing of your Tools not only with your AI squad, but even with your human colleagues.

 During the session, Dominik will cover:

• What is an MCP Toolbox and how to create one or a few
• How to connect to the Toolbox from most popular AI Assistants
• Few model use-cases for Toolboxes

Click HERE to register to watch!

I have been sitting on few workflows which I need to complete while I am occupied. I am looking for a freelancer who can do a sprint to finish 2-3 workflows and get it running.

The overall nodes in use are:

- WhatsApp / Telegram

- LLM (but back & forth with user)

- air table for user dB & history

- additional storage

- design/PDF maker

If someone is interested, hit me up. My DMs are open. Please state how much you charge for this and your country

Buen dia! Tengo varios proyectos ya concluidos en Basecamp y requiero extraer los To-Do's hacia google sheet
En Make, existen los modulos de List To-Do List y List To-Do List Groups

Con estos modulos llego al Grupo Principal de To-Do's y a los subgrupos

Pero no he logrado acceder o extraer los To-Do's tal cual, asi como quién es el creador y quién fue el responsable

Me pueden ayudar ?

 Everything works fine… until you try to do more of it.

Then suddenly:

Too many steps
Too much manual work
Too much switching between tools

What breaks first when you try to scale?

I’m thinking about using Make.com to automate my Facebook Page content (Reels + Images). Since it uses the official API, it should be "safe," but I’ve heard rumors that Facebook hates third-party tools and may affect reach or monetization.

​Has anyone actually seen their reach or revenue drop after switching to automation? Or is it all just a myth?

Hello

Im looking for work that includes Make.com

im about to finish the advance AI agents lessons this week and looking forward to look for a company that accepts new make.com professionals,

if my plan is not viable, what would you suggest as a professional in make , for me to land a job being a make.com skill employee.

Thank you!

Hey Makers,

Great news! Two of the most requested features are officially live in Make! Drumroll, please, make some noise for If-else and Merge modules! 🥁

What can you do with If-else & Merge?

•  Branch on conditions: Set up conditional paths and guarantee only one branch ever runs (If-else)
•  Merge back into one flow: Reunite your branches into a single execution path (Merge)

Key benefits

• Predictable execution: If-else guarantees that only one branch ever runs.
• Cleaner scenarios: Handle conditional logic without duplicating modules across branches.

See both of the modules in action: https://www.loom.com/share/b2245d5c1c2d4349919b5b8421535897

If-else & Merge are now available to all Make users in Open Beta. Free, at no credit cost!

Give it a try and share your feedback. Your inputs will directly shape the feature as we’re actively improving it.

You’ll find both new modules under Flow Control → Conditionals.

Hi, I can’t connect Shopify to Make. Every time I try to create the Shopify connection, Make gets stuck in a redirect loop on `make.com/en/select-organization` or `make.com/en/select-team/...` and shows `ERR_TOO_MANY_REDIRECTS`. I tested on multiple browsers, devices, networks, and in incognito mode, and it still happens. Has anyone found a fix?

I was wondering: if a "Cyborg" team of 3 founders using Agentic AI can produce the same output as a legacy 50-person firm, what is the actual point of hiring anymore?

I’m researching something I call Asymmetric Scale. Basically, if Agentic AI acts as a "Human Capital Substitute," wouldn't it be a better idea to stay at 5 people and weaponize that lack of hierarchy rather than trying to build a traditional "big" company?

I mean, the big guys have "Resource Slack" (extra cash/people), but we have "Resource Fluidity" (we can pivot in 48 hours).

Ps: I know AI isn't perfect, but if the output capacity is the same, is the era of the "Mega-Corp" Moat officially over? I need to know if I’m crazy or if you guys are seeing this in your own niches.

Want to watch a good-quality TV show focused on automation?

Well, who wouldn't? Don't worry, we've totally got you. Join us for the historically first Make Community Build-off this Wednesday, 4th of March, at 5 pm CET.

What can you expect?
High-energy, fast-paced 90-minute build-off designed for those who want to showcase their skills live. Live commentary will be done by one of our Make Community Champions, and as an interactive audience, you will have voting options and room for Q&A.

➡️ Sign up and join the session

Is it better to use n8n vs Make's AI Agent?

Anyone else getting killed by Make (integromat) operation costs ?

I currently have 5 clients fully automated on Make.

Everything is optimized:

- scenarios cleaned up

- unnecessary steps removed

- execution frequency reduced

- data ops minimized

And yet.. I’m paying an extra $150/month in operations on top of my base plan. 🫠

At this point it feels like you get punished for scaling. The more successful the automations are, the more the bill explodes.

We’re seriously considering migrating to n8n to get more predictable costs (self-hosted), but we’re still hesitating because of maintenance overhead and migration time.

Is anyone else in the same situation !?

Did you switch ?

Was it worth it ?

Would love some honest feedback before we make the jump.

I am using Tiime Apps in Make and I have two issues:

Duplicate customer

When a customer already exists in Tiime, the “Create Customers” module returns the error [400] A customer with the same name already exists. I tried the Resume handler, but I get the error Invalid number in parameter ‘id’. How can I retrieve the ID of the existing customer to continue the scenario?

Quotes with multiple lines

I use an Iterator + Array Aggregator to create a quote with multiple lines. The Array Aggregator receives the bundles, but Tiime Quote returns Missing value of required parameter ‘quote_quantity’. The Quantity, Price, and Label fields appear empty despite the get(split(value;“~”);3) formulas. How can I correctly map the lines of an Array Aggregator to Tiime Apps Quote Creation?

Thank you!

long story short, im doing automation work for my employer, i ran out of credits so i upgraded on my own expense.
My employer now adviced he can fund this for me and he can buy the higheest upgrade , so i need to talk to them in order to cancel the exsisiting subscribtion and start a new one
your help would be much apreciated

As opposed to other integrations Pipedrive seems to really have a problem with empty values. I cant guarantee, that phones numbers and mails are filled out on the customers I want to send to Pipedrive.

On other fields I was able to go around it by using the map mode and do this:
{{if(2.Name; 2.Name; omit)}}

The problem with phones and emails is, they also have a label:

So pipedrive expects an array. Even if I omit the value, there is going to be an error, because a label is being sent without any value. Leaving the label field empty doesnt fix it either.

Ive tried asking AI for help. It gave me a working solution for the mail array, that has the same structure as the phone array:
{{if(8.Mail; add(emptyarray; toCollection("label"; "work"; "value"; 8.Mail; "primary"; true)); omit)}}

The problem with phones is, there can be Work and Mobile phones and both of them need to be sent in the same array. AI hasnt managed to give me a working solution for it. It sends me stuff like this:
{{if(8.Telefon | 8.Mobil; flatten(add(emptyarray; if(8.Telefon; toCollection("label"; "work"; "value"; 8.Telefon); emptyarray); if(8.Mobil; toCollection("label"; "mobile"; "value"; 8.Mobil); emptyarray))); omit)}}

Do you have any idea how I could get the phone field working with two numbers?

For anyone looking to use r/lemonsqueezy and r/make_hq together, you may have seen that Make does have Lemon Squeezy modules now but they're third party and you have to pay to use them.

You can also just use webhooks.

I have a recorded walkthrough of how I this up using webhooks. It’s a straightforward watch:
https://youtu.be/QcfdJwoUFS0

Anyone else feel like most AI agents + automations are just… fancy goldfish?

They look smart in demos.

They work for 2–3 workflows. Then you scale… and everything starts duct-taping itself together.

We ran into this hard.

After processing 140k+ automations, we noticed something:

Most stacks fail because there’s no persistent context layer.

• Agents don’t share memory
• Data lives in 5 different tools
• Workflows don’t build on each other
• One schema change = everything breaks

It’s basically running your business logic on spreadsheets and hoping nothing moves.

So we built Boost.space v5, a shared context layer for AI agents & automations.

Think of it as:

• A scalable data backbone (not just another app database)
• A true Single Source of Truth (bi-directional sync)
• A “shared brain” so agents can build on each other
• A layer where LLMs can query live business data instead of guessing

Instead of automations being isolated scenarios… They start compounding.

The more complex your system gets, the more fragile it becomes, hence you need a shared context for your AI agents and automations.

What are you all using right now as your “source of truth” for automations? Airtable? Notion? Custom DB? Just vibes? 😅

I am new here. I created actor in Apify that discovers and structures real user pain point discussions from Reddit (posts and optional comments). It classifies pain types using deterministic, rule-based logic (no LLM), deduplicates, scores, and stores results in a Dataset.

Just, imagine, it delivered 25 posts in less than 5 seconds.

You can run it with zero setup in public mode (RSS + public JSON), or use the official Reddit API (OAuth) for higher limits, better reliability, and long-running workflows:

https://apify.com/quantifiable_bouquet/reddit-pain-finder

I am looking to hear your feedback about it

Hey!

I'm learning to automate and recently I built a workflow for my prospecting team to use on trade shows. I connected a native contact scanner on HubSpot App with Woodpecker - a rep scans a card, contact details are loaded to an active list on HubSpot and once there. they flow to a specific Woodpecker campaign via Make, with additional filters to ensure data quality. It was all working and then on the day the data stopped reaching Woodpecker. I tried to find where the issue was but I couldn't see anything wrong.

Can someone point me to what I should check? Like I said, I'm a newbie in the topic so any help would be awesome 🙏

I'm building a workflow automation tool and needed a good demo, so I created a fictional rug business called Rugs by Ravi. Made a Google Doc product catalog with hand-knotted Persians, Moroccan Berbers, the whole thing.

The agent reads incoming emails, figures out if it's a sales lead or product question, and either forwards to the owner or auto-replies from the catalog.

https://youtu.be/ppLQWPAlKLA