Hey there, do you want to hear about our new no-code/low-code platform?! It’s already becoming an arguably fairly tired proposition that’s wearing pretty thin on many in the IT industry. So what should we look for among the upstart start-ups now vying for a share of voice in this increasingly crowded market?
Looking for inspiration in the Holy Land is never a bad idea and it’s in Tel Aviv that we find Ply, a no-code customisation platform.
What is app customisation?
In its purest sense, application customisation is of course the work carried out by software engineers to align pre-existing platform technologies to specific customer use cases. A process that takes software away from its initial code and kernel structure and re-architects it for specific jobs and functions, this process often makes apps easier to use for the job intended but harder to support by the original platform developer.
That’s not what this is.
This is no-code application customisation to build custom internal features into the apps a business already uses. Instead of buying or building another app, Ply allows organisations to add contextual solutions into apps like Gmail, Zendesk, Salesforce, HubSpot etc.
Contextual connections
Co-Founded by the triumvirate forces of CEO Yaniv Tross, COO Zohar Sakal and CTO Guy Schlider in 2021, the company is focused on ‘contextual’ no-code solutions i.e. small pieces of software (logically named ‘features) that add feature functionality in-context inside other existing applications.
An example feature is add-ons, which enables no-code users (typically still software developers) to add buttons and interfaces inside applications and use data from the item the user is currently viewing, such as an email or a ticket.
Another feature type is notifications, which lets builders not only define when a notification is sent, but also create custom post-click functionality for approvals, feedback and quick contextual actions. Other features (all based on existing apps) include command bar tools, customer portals etc.
Three-ply to four-play
All these types of contextual customisations then add an additional layer to the applications taking them from (let’s say) two or three-ply thickness upwards to four-ply strength. Suddenly the company name makes sense, right?
“Over the last decade, countless low/no-code tools have emerged to allow the development of automations, tools and databases. While some use-cases require a new dedicated tool, most of the time having a contextual solution is 10x more effective. It’s more productive, faster to create, easier to onboard to and effortless to adopt. But mostly, it’s what users actually want,” said Yaniv Tross, Ply’s CEO. “Think about it this way, when a software company wants to solve a problem for its users, it doesn’t create an entirely new product. It adds a feature where the problem is. Ply is making this the reality for ops and internal product teams too.”
The contextual nature of Ply makes key use of AI. The company suggests that context awareness is one the biggest challenges in creating high-value AI applications. Aside from being context aware, the platform comes with a native integration to openAI, a prebuilt prompt interface and more tools to use contextual AI.
Ply’s permissioning and security controls let enterprise customers adopt fast continuous change, without the headache. The platform’s matrix approach to permissions allows IT teams to define the exact level of freedom builders have. without the risk associated with wide access.
Additionally, Ply’s Synced Groups makes it easier to manage permissions at scale. It allows admins to provide access to features based on permissions in the destination app, by syncing its permission structure back to Ply.
“We’ve seen an interesting process with nearly all of our customers, regardless of their size. They start with simple hacks to eliminate copying and pasting like ‘send ticket to Slack’, and within a few weeks, they’re building complex business logic into vendor apps – things like sales playbooks, employee onboarding and legal approvals,” said Tross.
According to recent suggested findings from magical analyst house Gartner, 70% of new applications developed by organizations will use low-code or no-code technologies by 2025, up from less than 25% in 2020. This shift reflects the growing trend towards no-code development, which allows users to create applications without the need for programming skills.
“We started out building Ply for Ops and IT, which are still our main customers [types of users], but we’ve quickly discovered that people in almost every role are building features. It’s an intuitive need – if you’ve ever said to yourself ‘I wish Gmail could do that thing’ then you get it,” added CEO Tross.
How does Ply work?
Users can click on the Ply extension in their browser, create a new add-on, connect an account, choose an element or context (such as a button in messages), design the button, save it, and then open the builder.
Tross explains that once the user enters the builder, they will be presented with three steps.
The first step is interfaces, which can be added directly to the workflow and allow the user to map data in a two-way street (input and output). Next is integrations, which are pre-made actions in different apps. The final step is helpers, which can help users manipulate data using functions like table functions, text functions, email template builder, and translation.
“After a feature is created, it can be shared with the rest of the team, ranging from one member to a hundred employees in an organisation. Ply also allows users to create multiple types of features. These include add-ons, which are added functions on apps; tools, which are available anywhere in a command bar, and custom notifications, a forthcoming feature that comes with actionable items,” he added.
It makes sense, most of us do wish that Gmail (or the other platforms Ply connects with) could do a whole handful of extra things. Ply isn’t promising to weed out the spam, reply automatically to all the invitations you obviously don’t want to take up or go to and filter through all the white noise to classify which items we should be concentrating on – but given the contextual AI approach that forms an inherent part of this story, that could be the next step.
13 hours ago
