From the inside: how Yapla is experiencing its own digital transformation

We often imagine that technology companies are best placed to ride the waves of innovation. They master the tools and trends and seem to be at the “peak” of digital maturity. And yet, the arrival of artificial intelligence reminds us of one thing: no organization has an automatic pass.

Yapla is a fast-growing SaaS company that serves more than 90,000 organizations around the world. For over ten years, we have made a simple promise: to help nonprofits streamline their management, centralize their operations, and save time so they can focus on their mission.

With the rapid arrival of artificial intelligence (AI), we had to ask ourselves some very concrete questions. How can we:

• understand its possibilities?
• accelerate innovation without weighing down our daily work?
• mobilize teams without creating anxiety?
• integrate AI where it adds real value?

In this article, I’m offering a unique behind-the-scenes look at a software company that, like all organizations today, is facing a major upheaval, specifically with the arrival of AI.

Through concrete examples, reflections from the field, and unfiltered introspection, I’ll draw parallels between the challenges faced by Yapla and those faced by nonprofits, regardless of their size or technological level.

How a tech company like Yapla integrates AI in concrete terms

Understanding AI simply, without technical jargon

AI, in our daily lives, is access to models capable of understanding our instructions and producing useful responses through text, data structures, analyses, sometimes code.

In other words, we describe a need as clearly as possible, and the model returns a usable output. This can be a draft email, an action plan, a summary of information, a structured table, or even a piece of code.

These models are progressing very quickly. They automate some of the work that used to take us time, especially repetitive or highly structured tasks. In a SaaS company like ours, this changes the speed of execution, but also the way we think about the “how” even before we act.

We can look at AI as part of a continuum. We've seen microcomputing, the web, mobile, and then the data era. AI is part of that continuum. It doesn't change our mission. It changes the means by which we accomplish it, and it forces us to learn faster than usual.

Three simple steps to get started in teams

We have chosen not to treat AI as an isolated project. We prefer to make it a daily reflex.

Here are the three initial steps we took at Yapla:

1. Make its use uncomplicated: We accept AI as a normal work tool. When it improves a text, an analysis, or a decision, that is exactly its role.
2. Adopt language models as everyday tools: ChatGPT, Claude, Gemini, and others are accessible to the entire team. The goal is simple: to allow everyone to work faster, without waiting for an official “AI moment”.
3. Explore the AI already present in our software: We test existing features, keep what really works, and learn what suits us. This testing ground is often the source of the best quick wins.

These three steps are a solid foundation for getting started on your own. And if you would like support in clarifying your direction or structuring a more ambitious project, our professional services experts can help you frame your approach and move ahead more quickly.

Internal conditions that support the movement

These steps only make sense if the company culture follows suit. We have therefore reinforced a few simple principles:

• innovation must remain useful and connected to the mission
• experimentation must be possible without micromanagement
• the right to make mistakes is normal
• curiosity is encouraged
• communication is constant

The human effects are visible and progressive. We are seeing:

• a reduction in guilt about using AI
• an increase in collective skills
• a more natural culture of experimentation
• greater confidence in our way of doing things
• a clear understanding of the benefits

AI First, AI Native, and AI agents: our integration method

Automating repetitive tasks to focus on value

Like all organizations, we perform repetitive tasks. They take time but do not always create direct value. For example, copying and pasting data, producing manual reports, sorting information, answering the same questions.

If AI handles these steps, we free up time for what really matters: analyzing, deciding, executing, supporting, and improving the product. Our rule is simple: automate the repetitive to focus on value.

At this stage, many nonprofits start with quick wins internally. But when the need involves a structural project (migration, transactional website redesign, member journey optimization, donations, or events), support from a professional services expert saves time and ensures the project achieves your goals.

Instilling the AI First reflex

AI First means that before starting a task, we ask ourselves how AI can help.

It often starts small, for example:

• turning a vague idea into a clear plan
• rewording a message to make it more readable
• summarizing a long document
• structuring data before analysis

Then, once the habit is ingrained, we move on to more advanced automation. The key point here is the reflex, not the complexity.

Create internal AI agents

Once repetitive tasks have been identified, we create agents. An AI agent is a specialized intelligence designed for a specific task. It understands a context, decides on an action, and then executes it.

We create them for measurable benefits and monitor:

• frequency of use
• time saved
• quality of results
• areas for improvement

This monitoring allows us to move forward quickly without getting sidetracked.

Becoming an AI Native organization

AI Native is the next step. We don't add AI at the end of a process. We integrate it from the outset.
This means that our processes and products are designed with AI in mind: what it can handle, what it can speed up, and what should remain human. This logic allows us to evolve without having to rebuild everything with each new development.

AI as an amplification of human work

Our position is clear: AI does not replace our work, it amplifies it. It helps us deliver faster and more consistently, and it frees up time for human, complex, and strategic work.

The three pillars of our AI strategy at Yapla

To structure our approach, we work around three complementary pillars.

1.Operational intelligence

a.Everything that improves day-to-day operations: support, finance, internal management, content production, recurring analyses.

2.IT intelligence

a.AI is transforming the way we develop, from analysis to testing, correction, and iteration. Our challenge is to make the most of IT to accelerate without losing rigor.

3.Product intelligence

a.We integrate AI directly into Yapla to create concrete value for nonprofits. As our customers centralize their data on a single platform, we want to enable them to use it in a secure and useful way.

This pillar-based structure helps us stay focused. The same logic applies to nonprofits: we start with operations, strengthen the tools, and then evolve the “product” in the broadest sense, i.e., your journey and your services. And if you want support with prioritization or implementation, our professional services can assist with a specific project, while you remain in charge of the overall direction.

Building and orchestrating AI agents

What is an AI agent?

An agent is a specialized intelligence with a specific mission, within a defined scope, with a clear objective.

Examples of agents at Yapla

We already have several concrete examples:

• prioritization of support tickets
• generation of management reports
• summaries of internal discussions
• automatic analysis of bugs to speed up resolution

The idea remains the same: remove the superfluous to give humans more time to decide and support.

Agent orchestration: how it works

Orchestration is the collaboration between several agents. Each agent plays a role in a chain.

For example:

1. one agent fetches the information
2. another cleans it up
3. another analyzes it
4. another produces a summary or takes a final action

We are gradually building this ecosystem, targeting the most repetitive tasks first.

Example: Yapla AI

Yapla AI (our AI support bot) is an agent that’s already in place. It answers users' questions based on our online support content.

Our goal is simple: to improve its understanding of the context and give it access to certain useful elements (billing, history, account information).

The objective is twofold:

• to respond more quickly to our customers,
• and to free up our teams for complex cases and human interaction.

In the same vein, semantic search is an example of “useful now” AI: it leverages existing data and simplifies access to resources.

And what actions do we recommend for nonprofits?

Nonprofits face challenges similar to ours. They have the same need to move forward in stages, the same tension between busy day-to-day operations and innovation, and the same need to stay aligned with their mission.

Our approach is transferable because it is progressive and concrete.

A 6-step approach to gaining digital maturity

• Conduct a diagnosis. Know where you're starting from.
• Provide clear direction related to the mission.
• Train and engage the team. Skills before tools.
• Simplify and automate repetitive tasks.
• Centralize and leverage data.
• Experiment over time, one step at a time.

One simple tip to keep in mind before trying to automate anything: take a moment to observe, test, and verify that it makes sense.

How Yapla can help you move forward at your own pace

At Yapla, our goal is simple: to enable every nonprofit to progress in your digital maturity at your own pace.

If you want to move forward independently, there are several free resources to guide you every step of the way: 

• Yapla AI
• online support
• Yapla Academy
• webinars
• email and video support 

And if you prefer to have an expert help you in your digital transformation, our professional services team is there to identify, collaborate and accelerate your structural projects. Specifically, we can help you clarify your direction and take action on topics such as:

• tool migration
• website redesign
• online store creation
• optimization of your member, donation, or event journeys

The idea is to save you time while building something solid that’s tailored to your reality.

Finally, for nonprofits that want to go even further, our partner Riposte provides support for overarching strategic planning. We're talking about digital strategy in the broadest sense, but also positioning, branding, and alignment between your mission, your organization, and your tech stack.

Conclusion

Digital maturity is a movement, not a state. AI is part of this continuum. It accelerates learning and amplifies what already works.

At Yapla, we integrate it as a reflex. With simple actions, a culture of experimentation, an AI First approach, agents, and AI Native logic.

For nonprofits, the principle is the same: move forward one step at a time, stay connected to the mission, and keep people at the center of it all.

In summary:

• AI is a new stage in digital transformation.
• We integrate it as a daily reflex, not as a separate project.
• Three starting steps: make its use uncomplicated, adopt language models, explore the AI already present in your tools.
• AI First, agents, and AI Native structure sustainable adoption.
• For nonprofits, a simple 6-step progression allows you to move forward without getting lost.

Pascal Jarry, CEO of Yapla