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Automating business processes with visual platforms like Make is more challenging than fitting two blocks together. Here, every little detail is of paramount importance: the architecture of scenario execution, the functionality of individual blocks, and the flexibility of their interconnections. If you're in the loop, you know what I mean. If not, you're about to get it.
We're still part of the Make community ourselves, having observed user requests for years. Often, we don't just observe, we live these needs too. It's from implementing these missing components that Latenode began, which now already has features that top the list of user requests from Make. Let's dive in.
This is one of the most popular requests. The essence is to have the ability to merge several scenario branches into one node. In some cases, this simplifies and speeds up scenarios, and in others, it's a critical requirement for implementation.
Suppose you have two data processing scenarios that share several common stages. Instead of duplicating work, you can simply merge these branches into one after performing each scenario's unique actions.
Case: Processing Survey Results
The trigger is receiving a new survey response. One scenario branch analyzes the responses and categorizes them, while the second updates statistics in real-time. At the end, both branches merge into one, which compiles the final survey report and either sends it to the database or alerts the responsible person.
Text parsing is an extremely useful feature when you need to extract specific information from a text body. On the Latenode platform, you can use a ready-to-go AI tool for parsing and analyzing such data, to pull out the parameters you need, and use them for further processing.
This is possible with the 'AI Text Extractor' module. On the left, you see the block setting window, on the right, the result of parameter identification from the text body.
Case: Customer Service Management
Imagine you manage customer service and receive inquiries in text format via various channels (e-mail, social media, feedback form on the website). Using the "AI Text Extractor" module, you can automatically analyze the text of each inquiry, extract key details (like the type of issue, specific details, customer contact information), and then use this information for automatic routing of the inquiry to the appropriate specialist or for report creation. This significantly simplifies request processing and boosts the efficiency of your customer service.
How your email looked before using the Latenode platform:
How it looks after:
Running a scenario with historical input data becomes particularly convenient in several cases:
Case: Testing Complex Automatic Scenarios
Imagine you are developing complex automation for processing large data arrays. During testing and debugging, an error might occur. Instead of manually recreating the input data and rerunning the scenario, on Latenode you can restart the scenario with the same input data with just one click. This accelerates the debugging process and simplifies testing, boosting the efficiency of your architectural development.
On Latenode, you can create your own blocks, which include entire scenarios. It's like putting together a toolkit that will then be used in any scenario. This significantly simplifies the process of creating complex architecture and saves you a lot of time.
Instructions for creating a custom module:
By the way, in the foreseeable future, we plan to launch a library of public modules from community members. This will not only simplify architectural development for new users but also provide creators of such tools with an earning opportunity for every use by other users.
So, we look forward to seeing you on our Discord server, where we share announcements and answer your questions related to no-code automation. We engage in interactive discussions there. Catch you soon!