Complex software.
Zero surprises.

Removing friction between people, systems and data.

Agile Labs designs, builds, integrates and modernises business software for organisations operating at scale.

Who we are

Agile Labs is a Singapore enterprise software engineering company. We design, build and secure enterprise software and AI systems. For more than a decade, we have built important software, including systems operating at national scale and in air-gapped environments.

We also assess whether software and AI systems are safe and ready to run. Software is easier to build than ever. Making sure it is safe to run is just as important.

Security is part of how we build from the start. We design for data protection, secure access and sound architecture throughout development. Whether we build the software or assess a system built by someone else, the goal is the same: software that is safe and ready to run.

We design, build and secure enterprise software and AI systems.

Engineering

We design, build and improve business software, from new systems to applications that need to be rescued or modernised.

Explore Engineering

Security & Assurance

We assess software and AI systems for security, risk and readiness for production, across systems built internally, externally or with AI.

Explore Security & Assurance

Team Extension

Our engineers inside your team, on your systems and your process.

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AI Workspace

Give your organisation one secure place to use AI, with control over models, data and access.

Explore AI Workspace

Selected work

Software other people depend on: platforms that run an operation worldwide, systems taken over from vendors who stopped delivering, and AI products tested before they met an enterprise review.

Insights

What we are learning from building, securing and running software and AI systems. Thirty pieces so far, written by the engineers who do the work.

Perspectives · AI

Why AI pilots fail to reach production

The two figures everyone quotes do not survive being traced. What the underlying studies do establish is where the failure sits: problem definition, data, deployment infrastructure, ownership and measurement.

1 September 2026 · 8 min read

AI systems

AI SECURITY

Testing AI agents for prompt injection

A test that ends at the model’s reply has established nothing. It ends at the action the system took.

4 Sep 2026 · 10 min

AI SECURITY

The attack that never touches the chat box

24 Jul 2026 · 8 min

AI SECURITY

Why a system prompt is not a defence

22 Aug 2026 · 6 min

AI

Evaluation and error rates

1 Sep 2026 · 9 min

Running it

OPERATIONS

Building an AI gateway

Routing is the least valuable thing it does. Identity, budgets, evidence and an off switch are the reasons to build one.

31 Aug 2026 · 9 min

OPERATIONS

Why a spend cap misses a runaway agent

22 Jul 2026 · 7 min

OPERATIONS

Who gets paged when the AI misbehaves

2 Sep 2026 · 7 min

OPERATIONS

Application recovery and deployment

23 Jul 2026 · 8 min

OPERATIONS

Why maintenance should improve software

13 Jul 2026 · 6 min

Engineering

SOFTWARE ENGINEERING

What AI changes about software development

A randomised trial found experienced developers 19% slower with AI tools, while believing they were 20% faster.

15 Jul 2026 · 7 min

SECURITY

Why scanners miss access control

16 Aug 2026 · 8 min

SECURITY

The licence problem in procurement

8 Jul 2026 · 7 min

SOFTWARE ENGINEERING

Why engineering continuity matters

2 Aug 2026 · 6 min

SOFTWARE ENGINEERING

What senior engineering requires

3 Aug 2026 · 7 min

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