Read the latest blogs, news and views from Infomentum.

A blueprint for project health monitoring using weighted milestones, Fibonacci estimation, and risk-informed progress tracking.

Every project manager (PM) gets asked the same question: Are we going to finish this project on time and on budget? To answer it, they usually would rely on delivery plans, burn charts, milestone trackers, and team estimates...

And whilst these tools are useful, they rarely provide the PM with a single, structured view that brings together delivery progress, budget consumption, and delivery exposure in a way that supports consistent judgement. Experienced PMs often develop a strong instinct for when something is drifting. That instinct is real and earned. But instinct alone is difficult to evidence, difficult to transfer, and difficult to defend when delivery confidence needs to be explained. That is the structural gap this framework addresses.

Policing organisations operate in one of the most demanding service environments in the public sector. IT services are mission-critical - any disruption, however small, can have a direct impact on frontline effectiveness.

At Infomentum, we’ve seen first-hand how IT Service Management (ITSM) functions within policing are under constant pressure. High volumes of requests - many of them low complexity - create a persistent challenge: how to maintain service quality while enabling IT teams to focus on more strategic priorities.

From my own experience as a senior police leader, the impact of this is very real.

Last night’s Digital Revolution Awards brought together organisations tackling real, practical challenges with technology. For our team, it was a brilliant evening to be part of.

It was great to reconnect with familiar faces, meet some new ones, and see first-hand the impact being made across so many different sectors. Moments like that are a good reminder of how much meaningful work is happening in this space.

And while we’ll try to stay modest about it… it made the night all the more special to be named winners of the ‘Excellence in Salesforce’ award for 2026!

As more organisations explore how AI can actually work inside Salesforce, Agentforce is quickly becoming a favourite. Unlike generic AI chatbots, Agentforce uses an organisation’s own internal knowledge base, including files, CRM data, case records, and process logic, to deliver answers that are accurate, contextual, and trusted. This allows you to build conversational experiences that feel natural to users while drawing on the full depth of your operational knowledge.

For this article, I wanted to go beyond the theory.

In the NHS pressure builds in waves. Winter surges. Capacity crises. Workforce shortages. Technology programmes that promised change but delivered more complexity instead, in a very similar way to what we have seen as a team with our work with the Police forces we’ve worked with.

Dr Simon Eccles has spent decades working in A&E, operating at the sharpest edge of the NHS. He has seen the demand for services, people unsure where to obtain the best care, and frustrated patients, whilst watching his colleagues try to do their absolute best. His perspective on digital change in healthcare is shaped by that experience. It is not abstract. It is grounded in what actually helps clinicians do their jobs and what impedes them.

Writing MUnit tests is something I do regularly as part of my MuleSoft development work, and like many engineers, I'm always looking for ways to work more efficiently without cutting corners. So when AI-powered features started making their way into the MuleSoft ecosystem, I was genuinely curious to see what they could do in practice. Test creation felt like the natural place to start, as it's a workflow I know well, which meant I could quickly spot where the tooling added value and where it still needed work.

One of those tools is the MuleSoft Dev Agent, which introduces a new way to create tests, using natural language prompts to generate MUnit tests directly from your MuleSoft projects. So in this walkthrough, we put the Dev Agent straight to work on a simple Hello World API and see how far it can take us, from generating MUnit tests in seconds to revealing where it really adds value.

What decades on the frontline reveal about system-generated demand, avoidable work, and where meaningful change really starts.

Dr Simon Eccles has spent decades working in A&E as a senior doctor and serving on countless boards across London. He is also a thought leader on the best technology for the NHS, and he sat down with us to discuss ways the NHS can improve its use of Salesforce. With all his years of experience, he has seen winter pressures come and go, targets change, restructurings repeat, and countless workforce initiatives introduced with good intent. His view is not theoretical. It is lived.

Introducing AI-driven solutions like Agentforce into UK policing is not a decision to take lightly. These powerful technologies have the potential to completely transform the way forces operate, from back-office efficiency through to frontline support. But with this power also comes new risks, particularly in how sensitive personal data is processed, stored, and interpreted. While these risks are real, the potential to deliver faster, fairer, and more effective policing outcomes makes their careful navigation worthwhile.

In an environment governed by high standards of public accountability, ethical scrutiny, and strict legal obligations under the UK GDPR, Data Protection Act 2018, and Law Enforcement Processing provisions, a Data Protection Impact Assessment (DPIA) is not just a formality - it's essential. It provides a defensible framework for making informed decisions, protecting officers and the public alike.

The British model of policing has always rested on a delicate balance: local accountability, national legitimacy, and public consent. The Government’s proposal to create a National Police Service is the most radical attempt in a generation to rebalance that system for a digital age.

Having witnessed three decades of change in the police service, and as a retired senior officer, at first glance, the Home Office’s White Paper, From Local to National: A New Model for Policing, is about structures - fewer forces, clearer leadership, stronger central coordination.

Every public sector leader I speak to wants to unlock the promise of artificial intelligence (AI). The ambition is clear: to deliver services faster, give staff back precious time, and improve experiences for citizens. The challenge is that budgets are tight, scrutiny is high, and no one wants to waste money on the wrong investment.

That tension often leads to the question… how much should we actually spend on AI?