Technical Debt easy EBITDA for Private Equity

Private equity houses like buying organisations that carry technical debt. The debt is priced into the deal, and the cost of carrying it sits in the run rate: licences, hosting, maintenance contracts, and the people needed to keep old systems alive.

Remove the debt and that spend is freed. It drops straight to EBITDA, which makes it some of the easiest value in the plan to go after.

AI makes the migration viable

AI has changed what a legacy migration costs. Codebases that were too large, too old, or too poorly documented to move can now be analysed, transformed, and migrated onto modern, cheap, scalable platforms.

The same applies to a full re-write. Applications that were maintained in place because rebuilding them was uneconomic can now be re-written as modern scalable APIs. That clears the technical debt at source.

AI brings its own risk

Speed introduces new exposure. Headless generation puts code into a codebase that nobody reviewed. Intellectual property can leave the business through the tools themselves. Process governance breaks down when output runs ahead of the controls around it.

In heavily regulated environments, these become the deciding issues. You have to show an auditor how a change reached production, who approved it, and where the code and the data went on the way.

How Claranet helps

Claranet helps in two ways. Most portfolios need both.

Managing and hosting heavy application workloads

We manage and host heavy application workloads across a range of sectors, and particularly across highly regulated ones. We host on AWS, Azure, and sovereign cloud, and we keep the hosting resilient, secure, patched, and supported.

As and when it is required, we replatform onto modern Kubernetes architecture, aligning the software, images, and technologies underneath it. That alignment drastically reduces the cost of management. It also changes what you back up: the databases, with everything else held as infrastructure as code (IaC).

An AI-enabled development team

The second route is our development team. They have been building and refactoring applications for years, increasingly with AI.

They do not vibe code. The code is heavily governed, and it is written at the speed and scale that AI allows.

Why the process decides the outcome

Garry Kasparov, drawing on what advanced chess taught him about people working alongside machines, put it this way:

'A weak human player plus a machine plus a better process is superior to a very powerful machine alone, and, more remarkably, superior to a strong human player plus machine plus an inferior process.'

That is the argument for how we work. The process wrapped around the model decides the outcome, so that is where we put the engineering discipline: review, release control, audit evidence, and clear ownership of where code and data can go.

Where to start

Start with what each asset is carrying and what it costs to carry. That tells you which debt is worth clearing first, and whether the work sits in the hosting, in the code, or in both. Talk to us about a portfolio review.