P92 Digital - a Gloster Group Company

13/08/2026

Your platform can run AI. Being ready to run it in production is another job.

Most enterprises already run on infrastructure that can handle AI. Azure, a modern edge stack, Cloudflare in front of it. The compute is there. The gap sits one layer up, in the operations that make an AI workload safe to run in production.

An AI prototype that works in a demo is not the same asset as one running live. Someone has to own the API keys. The logs have to go somewhere you can query. When an agent calls an internal system at 2am, a human needs to see it, scope it, and stop it if it misbehaves. That layer rarely appears in the original budget.

This is the work of an AI Operation Partner. We take an AI-capable estate and make it AI-ready: identity scoped to each agent, observability on every call, rate limits and secrets management, governance that stands up to an audit. Then we run it as a managed workload.

The commercial point is simple. The same Gloster team delivers more per engineer hour using AI-supported workflows, so your engineers stay on architecture and the plumbing stays with us. One accountable partner for the platform, the pipeline, and the 24/7 support behind it.

If you have an AI prototype heading for production, map the operational gap before it ships, not after the first incident.

Have an AI prototype heading for production? Book an architecture review and we will map the operational gap before it ships.

12/08/2026

The app was ready in two weeks and the demo works. So why couldn't it go live?

Last week we sat down with a scale-up team. In two weeks they had put together an AI-assisted app, it worked in the demo, and the investor had also seen it. Their question was simple: can it go live on Monday?

It couldn't. And not because the code was bad.

A quickly assembled prototype comes apart in exactly the places a demo never visits. Five hundred concurrent logins. One malformed input that nothing catches. A database half the team can access, with no record of who changed what. A demo gives you no answer to these. Production gives you one at the first real load.

That is why we run a structured engineering review before anything goes to production. Led by a senior architect, in just five working days, at a fixed price from EUR 2,500. We work through six areas: security, architecture, scalability, deployment, observability and compliance. The outcome is an itemised, prioritised risk register: where the risks are, how significant they are, and in what order they are worth fixing.

If needed, the Fix Sprint, the production implementation and ongoing operations follow.

Gloster Digital Group brings 20+ years of enterprise software development, with UK, DACH and CEE delivery. We work under NDA, and on-prem reviews are available.

Vibe coding is worth using well. The prototype is your achievement. Whether it can go live is a measurable question.

I would like to request a Vibecode audit:
https://glosterdigital.com/en/vibe-code

11/08/2026

An IT partnership lasts for years. Transparency matters. 📊

Gloster is listed on the Budapest Stock Exchange (BSE: GLSTR), giving partners access to audited, regularly reported company information. This is not a marketing claim. It is how we operate.

What we commit to can be verified: https://glosterdigital.com/en

10/08/2026

A 15-year-old system is rarely beyond saving. Rebuilding it is the bigger risk.

The instinct, when a system has run for 15 years, is to assume it is beyond saving and start again. In our experience that is rarely true.

A business-critical application is more than source code. It holds years of accumulated business logic, specialised processes and dozens of integrations. Replacing all of it carries technical, commercial and organisational risk that a live, daily-operation system can seldom absorb.

We worked with the German Red Cross (DRK) on its laboratory information platform. The system connects lab equipment from different manufacturers, handles sensitive health data, and supports work where a few hours of downtime is simply not an option. Early on, one of their team asked a question we still repeat: what happens if this system goes down for even an hour? The answer was human, not technical.

So we modernised in steps rather than rebuilding from scratch. Docker, Kubernetes and a microservice architecture, chosen for specific problems, not because they were fashionable. New labs spin up in minutes. New functions ship without downtime. The results in live operation:

70% fewer manual data-entry errors
60% faster sample processing
99.9% availability

The wider lesson holds across automotive, manufacturing, finance and the public sector. Healthcare providers do not have to choose between innovation and operational continuity. With the right strategy you get both.

Before you sign off a full rebuild, ask whether the existing system can be evolved instead: https://glosterdigital.com/en/insights/software-modernize-or-rebuild

When is it a good idea to modernize business-critical software, and when is it worth rebuilding it from scratch? What the German Red Cross’s digitization project taught us

06/08/2026

"About two weeks." - This is the sentence that kills most projects.

A bad estimate rarely fails on the development side. It is decided at the planning stage, when someone glances at a half-page description and says a number off the top of their head. Then the pilot stalls, because the scope turned out to be twice as big as the first estimate.

EstiMate AI addresses exactly this point. The plugin, built into Jira, provides time-based estimates for development tasks, along with a written rationale and a task breakdown. What comes out of it is not a single number, but a transparent logic explaining why the figure is what it is.

What this means in practice as a project manager: the planning cycle gets shorter, the decision can be made sooner, and project risk decreases measurably, because the scope is visible right at the start, not after the first sprint.

Accurate estimation is the cheapest risk management there is. No separate tool, no separate person, no separate contract. Just a clearer picture of what you are getting into.

If you are planning a larger development project right now, it is worth seeing what an AI-supported estimate looks like on your own Jira board.

One click on the Atlassian Marketplace - and your next estimate will no longer be a gut feeling:https://glosterdigital.com/en/estimate-ai

05/08/2026

Anyone can build with AI. But will your system be production-ready?

AI can build a working app in days now. The requirements for going live have not moved an inch.

Generated code often behaves nicely on the happy path. The harder questions arrive later: how does it handle failures, how much load will it take, are the permissions right, and can you see what happened during an incident?

That is why we built the Gloster AI Readiness Audit.

Our senior architects assess whether the application is genuinely ready for production, then produce a prioritised action plan covering the risks that matter most.

Fast development is table stakes now. Production readiness is still an engineering discipline.

Book a Gloster AI Readiness Audit and get a prioritised action plan on your production risks.

04/08/2026

The developer delivers the code, then disappears before anything can go wrong. Sound familiar? 🔄

The software lifecycle does not end at go-live. That is where it really begins: operations, support, continuous development and security. A partner who only builds, takes responsibility for only half the outcome.

Gloster takes responsibility for the entire lifecycle, from planning to operations. One partner. One accountable team. There is no need to coordinate between development and operations because the same team handles both.

See what end-to-end partnership looks like: 👉 glosterdigital.com/en

03/08/2026

AI-capable is not AI-ready. Nobody has budgeted for that gap.

After modernisation, your code can talk to the model: an API, a clean pipeline, a service that takes a prompt and responds. That is the half any project of this kind delivers anyway.

The other half sits in the runtime underneath. Stable, under load, controllable at the edge, secure by default, fast enough for inference. These are properties of the infrastructure, not the code.

Refactoring does half of the job done, and then it stops. The rest is a platform decision, and it becomes expensive if it is made too late.

That is why the conversation has shifted towards edge platforms such as Cloudflare: governance, security and performance are already in place there, as a global network.
Cloudflare blocks over 230 billion cyber threats every day (2026 Threat Report). Building a network like that yourself takes years. Adopting one works from day one.

In the article we walk through two patterns we see in every project: a governed AI access layer in front of your existing models, or building and running AI directly on the platform. We also write openly about why Cloudflare's handling of its worst outage since 2019 is more convincing than a spotless uptime record would have.

Where does your IT landscape sit between AI-capable and AI-ready?

Read the full article on why prompt security is a platform decision, not a refactor:
https://glosterdigital.com/en/news/ai-capable-is-not-ai-ready

30/07/2026

A working system can still be your biggest business risk. ⚠️

Legacy software rarely fails all at once. It erodes speed, cost efficiency and delivery capacity over time: maintenance grows, developers who understand it become scarce, and every new requirement gets stuck on an outdated architecture.

The question is not whether the system runs today, but whether it can carry tomorrow's plans.

The software lifecycle only truly begins after go live. Operations, monitoring, security updates, continuous development and NIS2 compliance are not optional extras. These are the areas where a system either continues to create value or quietly deteriorates.

That is why every modernisation we do starts with an audit:
👉 glosterdigital.com/en/software-modernisation

28/07/2026

Administration. Data handling. Routine checks.

These are consuming your experts’ time and leading to slower decisions and overloaded teams. 🤖

AI creates real business value when it removes repetitive work and gives capacity back to your people for decision-making, innovation and customer relationships.

Development and operations are treated as two separate worlds, with separate teams and separate owners. Between them sits a familiar grey area where incidents get lost, documentation is incomplete, and no one knows exactly who is responsible.

See where AI can unlock capacity across your organisation:
👉 glosterdigital.com/en