Case studies

Nimblr accelerates development with AI: 3x growth in shipped code changes

Investment year: 2023

Customers: 4,500+ organisations across Europe

Industry: IT security awareness and training

A snapshot

Nimblr is a holistic IT security awareness platform that helps organisations strengthen their security culture through automated, personalised training. Built on behavioural science and powered by threat intelligence, Nimblr's SaaS platform combines micro‑learning, realistic simulations, instant feedback and measurable reporting in one seamless experience.

Getting started with AI coding: From inspiration to new ways of working

Like most ambitious SaaS companies, AI was high on Nimblr's agenda. The management team saw clear opportunities to accelerate development and stay ahead of the competition by applying AI across different parts of the business.

Inspired by other Monterro portfolio companies and their shared learnings through Monterro's Infuse AI programme, Nimblr took a structured first step: defining a company‑wide AI policy.

While a handful of developers had already been using AI tools for several years, there was no shared framework, routines or ownership in place. The AI policy clarified expectations, roles and responsibilities – a critical foundation for building trust across the team.

“Once we had the AI policy in place, we rolled out Claude licences to everyone and encouraged developers to start experimenting in their day‑to‑day work. The policy is essential to give people confidence and courage to test new ways of working, especially in a security-focused business like ours.” - Martin Prieto, CTO at Nimblr

The developer's new role in the AI era

As the development team began using AI for coding, output increased rapidly. It soon became clear that existing workflows and approval structures were not designed for this new reality. Production‑ready code was piling up in review queues, creating bottlenecks and delaying releases to customers.

“To turn increased production into real business value, we had to redistribute ownership and responsibility, enabling the team to move faster while staying in control.” - Martin Prieto, CTO at Nimblr

Workflows and checklists were updated to define which types of releases required approval at different levels. At the same time, the role of the developer evolved significantly.

Today, developers take far greater ownership and a more holistic responsibility for each assignment. Previously, tickets often came with detailed specifications and developers acted primarily as executors. Now, they spend more time collaborating with Claude to analyse the problem, explore solutions and define scope – writing less code themselves.

“Most of our developers are full‑stack, so taking on more responsibility is a natural next step. Today, they don’t just deliver what’s in a ticket. They analyse the assignment together with Claude – what needs to be done, how to do it and how to scope it. One developer working with AI can now deliver more than a team of two or three could before.” - Martin Prieto, CTO at Nimblr

AI has also enabled developers to work more independently. With Claude as a constant companion, many problems can be solved individually. This new autonomy, however, also introduced a need for stronger alignment to avoid duplicated efforts – reinforcing the importance of communication, transparency and shared understanding across the team.

The challenges: Building trust and security

Not everyone was convinced from day one. While some developers were early adopters, others were more cautious. At Nimblr, a few key individuals stepped up as AI ambassadors – sharing hands‑on experiences through internal workshops and everyday collaboration.

Together with leadership, they actively listened for concerns and feedback in day‑to‑day work, addressing issues quickly and translating insights into updated workflows and checklists.

“It’s crucial to let people take small steps and to genuinely listen to their concerns. When you build that feedback into policies and processes, you create a structured and secure way of working with AI – and trust follows.” - Martin Prieto, CTO at Nimblr

The results: Faster development, a shrinking backlog and stronger roadmap

The impact of Nimblr’s AI initiative goes far beyond faster code generation. In just four months, the team fully embraced AI tools to boost both internal productivity and customer delivery.

The merged number of pull requests – code changes released to production – nearly tripled quarter-over-quarter, from 91 in Q4 2025 to 242 in Q1 2026.

This acceleration has also allowed Nimblr to significantly reduce a long‑standing backlog. From a steady level of roughly 150 tickets, the backlog is now down to 30 – and continuing to shrink.

“We can fit so much more into our product roadmap. Just one week into the new quarter, we realised we could deliver 50% more releases than planned. That allows us to be far more ambitious in our roadmap planning.” - Martin Prieto, CTO at Nimblr

Beyond coding: High‑speed, high‑quality content production with AI

With development teams spending less time on manual coding, Nimblr also explored new AI use cases beyond engineering. One result is a new internal tool supporting content creation.

Nimblr’s security awareness courses and personalised training content are continuously updated to stay relevant and localised across regions and languages. During the first quarter alone, the new AI‑powered content engine enabled one person to produce the same volume of content that previously required three people plus a professional translator for an entire year.

The tool includes a translation memory tailored specifically to security awareness, ensuring both consistency and accuracy. Productivity has increased dramatically, while content quality has improved.

Key AI achievements in just four months:

3x growth in code changes shipped

Backlog reduced from 150 to 30 tickets (and falling)

12× faster content production

50% more features added to the product roadmap

New AI module launched, enabling customers to tailor course content

What's next: AI agents and faster product development

Encouraged by the early results, Nimblr continues to refine its ways of working and explore new AI use cases across the business. One focus area is transforming existing checklists into AI agents. Another is using AI to rapidly turn product ideas into prototypes – significantly shortening development cycles.

“AI gives us the time and space to explore new ideas. With Claude, we can move from idea to prototype and testing within the same day.” - Martin Prieto, CTO at Nimblr

From a product perspective, Nimblr will continue to introduce AI‑powered capabilities where they add real customer value, while also helping organisations address the growing AI‑related threat landscape in IT security.

Advice to SaaS companies starting their AI journey

Based on Nimblr’s experience, Martin shares three practical lessons for other SaaS leaders:

Identify AI ambassadors. Let them experiment, share learnings and lead adoption. Provide licences early to enable hands‑on experience in a controlled way.
Respect that change is hard. Create space for concerns and feedback, then embed them into policies and workflows to build trust.
Stay grounded in your business. Don’t apply AI for the sake of it. Anchor initiatives in your core values and customer needs to ensure meaningful outcomes.