Client Experiences

Hear from organisations that have worked with us to explore and implement artificial intelligence capabilities.

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Client Success Stories

What Clients Say

Feedback from organisations we've had the privilege of supporting.

KT

Kai Tan

Head of Operations, Logistics Firm

Singapore

"The readiness assessment helped us understand where we actually stood regarding AI capabilities. The team was honest about what made sense for our context and what didn't, which I appreciated."

January 2026

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Sarah Ng

CTO, FinTech Startup

Singapore

"Working with Syntelix on our credit scoring model was a collaborative experience. They involved our data team throughout, and we now have a system we can maintain ourselves. The documentation was thorough."

December 2025

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Rajesh Lim

Director of Innovation, Healthcare Provider

Singapore

"The advisory service has been valuable for navigating vendor claims and understanding what's feasible within our regulatory constraints. Having experienced practitioners to consult has prevented several missteps."

February 2026

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Michelle Wong

VP Strategy, Retail Company

Singapore

"The demand forecasting model they developed has been running reliably for six months now. What stood out was their focus on making it work within our existing systems rather than requiring major infrastructure changes."

January 2026

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Ahmad Chen

COO, Property Management

Singapore

"They helped us understand which of the various AI tools we were considering actually aligned with our needs. Saved us from investing in capabilities we wouldn't have used effectively."

December 2025

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Jennifer Lee

Data Science Lead, E-commerce Platform

Singapore

"The knowledge transfer sessions were particularly helpful. Rather than just handing over code, they ensured our team understood the reasoning behind key decisions and how to troubleshoot common issues."

February 2026

Success Stories

Detailed examples of engagements and their outcomes.

Challenge

A logistics company was experiencing delays in route planning due to manual processes. They had five years of operational data but weren't using it to optimise decisions. Their team lacked experience with predictive analytics.

Solution

We conducted a readiness assessment to evaluate their data quality and infrastructure. Following this, we developed a route optimisation model that considered historical traffic patterns, delivery windows, and vehicle capacity constraints.

Results

After three months of testing and refinement, the system reduced average delivery time by eighteen percent and fuel costs by twelve percent. The operations team now manages the system independently.

"The measured approach meant we could validate results before full deployment. This built confidence across the organisation."

— Operations Director

Duration: 10 weeks • Completed December 2025

Challenge

A financial services firm wanted to enhance their fraud detection capabilities but was concerned about false positives affecting customer experience. They needed a solution that balanced security with usability.

Solution

We developed an anomaly detection model that flagged unusual transaction patterns while considering individual customer behaviour. The system included adjustable thresholds and clear explanations for flagged transactions.

Results

Detection rate for suspicious activity improved by twenty-four percent while false positive rate decreased by thirty-one percent. Customer complaints related to transaction blocks fell by forty-two percent.

"They helped us think through the compliance implications from the start, which prevented issues during our regulatory review."

— Risk Management Head

Duration: 12 weeks • Completed January 2026

Challenge

A healthcare provider wanted to reduce patient wait times but struggled to predict appointment duration accurately. Historical scheduling data existed but wasn't structured for analysis.

Solution

We first helped organise and clean their appointment data, then built a duration prediction model considering appointment type, patient history, and physician patterns. The system integrated with their existing scheduling software.

Results

Average wait time decreased by twenty-two percent over four months. Schedule adherence improved, allowing the clinic to serve an additional fifteen patients per week without extending hours.

"The data preparation phase was crucial. They helped us establish processes that continue to improve data quality for future initiatives."

— Clinical Operations Manager

Duration: 9 weeks • Completed February 2026

Track Record

Some numbers that reflect our experience supporting organisations with AI initiatives.

4+
Years of Operation
28
Organisations Served
4.6
Average Client Rating
82%
Client Return Rate

Get in Touch

Address

8 Shenton Way, #36-04
AXA Tower
Singapore 068811

Office Hours

Monday - Friday: 9:00 AM - 6:00 PM
Saturday: 10:00 AM - 2:00 PM

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We'd be happy to discuss your AI initiatives and explore whether our services might be helpful.

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