Published: Jul 08, 2025

Design AI that works — and pays off

AI has captured the imagination of every business leader. But too often, projects stall between ambition and execution.

The reason? Poor design choices were made too early, without clear value metrics or consideration for operational realities.

At NCS, we believe good AI doesn’t happen by chance — it’s engineered by design. That’s why the third and fourth steps of our transformation approach focus on one thing: Getting the design right and making the ROI real.

By helping clients plan, scope and evaluate their AI systems with clarity, we avoid wasted effort and accelerate time to impact.
 

This stage is where vision meets discipline. Our teams work closely with clients to define the right AI features for the problem at hand while estimating the real-world value of what’s being built.

We look beyond model benchmarks to understand how AI will perform in your environment, at scale, under constraints.

Through our AI Design and ROI Planning framework, we help answer five essential questions:

    • What should the AI system do — and not do?
    • How will it run in your tech stack and workflows?
    • What does success look like in cost, speed and quality?
    • Is it secure, explainable and future-ready?
    • And is the ROI clear before we build?

To guide this, we evaluate design trade-offs across four pillars:


 

In a live customer contact centre, thousands of service calls were being handled each day. Supervisors needed better visibility, agents needed less admin and customers wanted faster answers.

We introduced a speech-to-text (STT) solution that could transcribe conversations in real time, understand local accents and summarise interactions for downstream use.

But the real breakthrough was not just what the model could hear — it was how the system was designed to work across a complex, real-world environment:

• Security: Audio data was processed within a private cloud environment with strict access controls, anonymisation protocols and full audit logging.
• Performance: Optimised STT models were selected for low latency, even under overlapping speech. The result: Fast, accurate transcripts that kept up with the pace of live calls.
• Cost: We shortlisted open-weight models like Whisper and our own NCS Ins8.ai STT engine, which offered commercial accuracy without ongoing subscription fees, lowering the total cost of ownership.
• Portability: The transcription engine was integrated easily into the contact centre’s telephony systems. No rip-and-replace, just a seamless layer of intelligence over what was already in place.

The impact? A 54% reduction in after-call paperwork, faster issue resolution and richer insights for quality assurance teams. Agents could focus on people, not note-taking, and the organisation built a strong foundation for voice-based automation in future phases.
 

A development team struggled to resolve performance issues buried deep in legacy Java code.

Rather than expand the QA team, an AI agent was trained and deployed to spot SQL inefficiencies like repeated queries inside loops or unindexed joins.

But the real impact came from the design:

• Security: Source code never left internal networks — models were run in  a controlled environment.
• Performance: Lightweight open-weight models ensured fast analysis, enabling faster feedback for developers.
• Cost: No high-priced licenses, just smart model selection and fine-tuning for the task at hand.
• Portability: The agent was embedded into the CI pipeline, working seamlessly with existing tools.

The result? A 40% reduction in code review time and a measurable drop in database latency — translating directly into business value.
 

Many AI initiatives fall short not because the technology is lacking, but because design decisions were not grounded in real operational needs.

Before committing to a model or solution, it is important to take a step back and ask: What are we really solving for? What will success look like in practice?

We have developed practical toolkits based on real-world applications to help organisations navigate this stage with clarity, balancing performance, cost, security and future readiness.