DeepInspire

Happy Vyshyvanka Day from the DeepInspire team! 🇺🇦

We’re excited to share a new case study!

Risk teams are under growing pressure to process more information and respond faster to emerging threats.

In our latest case study, we share how DeepInspire helped a Switzerland-based AI company build an AI-powered risk management platform for leading financial institutions.

The platform combines generative AI with large-scale financial datasets to help investment, risk, and compliance teams identify emerging risks and make faster, more informed decisions.

Read the full case study: https://deepinspire.com/ai-powered-risk-management-platform-for-financial-institutions

We’re excited to be featured in TechTimes!

In this article, DeepInspire CEO Pavlo Terletskyy talks about something we see again and again in real projects.

“90% done” rarely means what it sounds like.
It’s where systems meet real-world conditions, and where hidden complexity starts to show.

Take a look, we’ve shared our experience and practical advice on how to navigate this stage: https://www.techtimes.com/articles/315964/20260417/90-trap-why-software-projects-stall-when-they-seem-almost-done.htm

DeepInspire turns 26 today.

We’re grateful to everyone who’s been part of this journey – our team, clients, and partners along the way.

To celebrate, we decided to do something special this year and released a limited edition DeepInspire wine in collaboration with the Ukrainian winery Fathers Wine – proudly grown and crafted in Ukraine. A small way to capture the spirit of the journey we’ve been on.

Looking forward to what’s ahead. Onwards and upwards!

As manufacturing businesses scale, maintaining control over inventory becomes increasingly complex – particularly when operations span multiple locations and involve high-value assets.

For Baird & Co, the UK’s largest gold refiner, this meant moving beyond manual processes towards a more structured and reliable approach.

We worked closely with their team to design and deliver a custom inventory management platform tailored to their operational and compliance needs.

The platform enables:
• Real-time tracking across multiple vaults
• Complete movement history for audit and compliance
• Faster, more confident order fulfilment decisions
• Improved production planning and resource allocation
• Reduced reliance on manual processes

A key focus throughout the project was not to replace existing expertise, but to support it with systems that make everyday work easier and more reliable.

Discover the full case study: https://deepinspire.com/custom-inventory-management-solution-for-baird

Happy Easter from all of us at DeepInspire!
Wishing you a relaxed, enjoyable weekend and time well spent with those around you.

Regulated environments don’t leave much room for ambiguity. Decisions need to be clear, traceable, and defensible – whether you’re dealing with fraud detection, onboarding, or risk scoring.

This is what Explainable AI (XAI) is really about.

It’s not a different type of model. It’s the ability of a system to show how a decision was made – what data was used, which factors had the most impact, and how the outcome can be justified if questioned.

In practice, that means:
🟣 you can trace a decision end-to-end
🟣 you can explain it to a non-technical stakeholder
🟣 you can validate it during an audit

Without that, AI becomes very hard to use in regulated processes, no matter how accurate it is.

Explainability is what turns AI from a black box into something a business can actually rely on.

Discover more in our latest article on Explainable AI in finance: https://deepinspire.com/blog/explainable-ai-in-finance-what-is-xai-and-why-its-critical

Great news today.
DeepInspire is now ranked by Techreviewer among the Top Software Development Companies in the UK!

Proud of our team. Grateful to our clients. Excited for what’s ahead.

Before we start development, we run a proper discovery phase.

In complex operational projects, the biggest risk is not technology. It’s building something that looks correct on paper but doesn’t fit how the business actually works.

Discovery is where we prevent that.

We analyse existing workflows end-to-end. We map how data moves across departments. We identify manual steps, control points, edge cases, and compliance dependencies. We look at what breaks when volume increases and where decisions rely on informal knowledge.

Then we translate that operational reality into system architecture, data models, and clear functional boundaries. We make deliberate decisions about what the system must handle (and what it should not).

Only after that we move into development.

Discovery is not documentation for the sake of documentation. It’s how we reduce risk before writing code. It’s how we make sure the system we build replaces friction, not just digitises it.

For us, good software starts long before the first sprint. It starts with understanding the business well enough to design infrastructure, not just features.

UK vs EU AI regulation: what businesses need to know in 2026

AI regulation is no longer “something legal will figure out later.”
For leadership teams, it’s becoming a strategic and operational issue.

The EU has taken a prescriptive route with the EU AI Act - clear rules, risk categories, and real penalties (up to 7% of global turnover). The UK, meanwhile, is betting on a principles-based, pro-innovation model, enforced through existing regulators.

Both aim for responsible AI, but for businesses operating across borders, the differences matter - a lot.

In our latest article, we break down:

🟣 how the EU AI Act actually works in practice

🟣 what the UK’s “flexible” approach really expects from companies

🟣 why UK-based businesses are still affected by EU rules

🟣 what leadership teams should do now (before enforcement tightens)

If your company uses AI in areas like finance, HR, customer decision-making, analytics, or automation, this is worth a read.

Read the full article here: https://deepinspire.com/blog/uk-vs-eu-ai-regulation-what-businesses-need-to-know-in-2026/