Client Experiences
What Firms Say After Working With Us
We have collected feedback from clients across manufacturing, financial services, and professional practices in Malaysia. These are their accounts of what the engagements produced and where things could have been better.
Back to HomeReviews
Client Feedback
Zainal Ariffin
Head of Operations, Klang Valley Manufacturing Firm
We brought Cendana Tech in to build a demand forecasting system for our production scheduling. What I appreciated most was that they read through our data first and told us where it had gaps before writing a line of code. The final model does not cover every scenario — they were upfront about that — but for the 80% of cases it was designed for, it works well and our planning team uses it every week.
April 2025 · ML Pilot
Tan Li Wen
CFO, Petaling Jaya Financial Services Firm
We commissioned a Data Readiness Assessment before committing to a larger project. The report was direct — it identified three data sources we thought were usable but were not, and gave us a clear sequence of steps to fix that. It took some months to work through their recommendations, but when we eventually ran the pilot, it went smoothly because the groundwork was in order. The assessment paid for itself.
March 2025 · Data Assessment
Nor Izzati Mahmud
Director, Professional Services Practice, Subang Jaya
Our board wanted to understand what AI could actually do for a firm our size before making any spending decision. The Leadership Reading Session was exactly what we needed — three hours, three worked examples from comparable practices, and a written summary of the questions we should be asking. No sales pitch. The facilitator was direct about what the technology cannot do, which was what convinced our board to take the next step.
April 2025 · Leadership Session
Raj Kumar
General Manager, Penang Electronics Manufacturer
We had tried twice before with other providers to build a defect classification system and both times ended up with something our quality team did not trust enough to use. Cendana Tech's approach was different from the start — they set the success criteria with us before touching the data. The system they delivered is now part of our QC process. It flags items for human review rather than replacing the reviewer, which is the right design for our line.
February 2025 · ML Pilot
Siti Hajar Yusoff
Head of Strategy, GLC, Kuala Lumpur
The assessment gave our leadership a realistic picture of our data situation for the first time. Until then, different departments had different beliefs about what data we held and what quality it was at. The Cendana Tech report settled that with evidence. The recommendations were sequenced well — not a wish list, but an order of operations that matched our resourcing. We have completed two of the five steps they proposed.
March 2025 · Data Assessment
Lim Chin Keong
Managing Partner, Johor Bahru Law Firm
I attended the Leadership Reading Session with three of my partners, all of us sceptical about AI claims we had heard from vendors. The session did not try to sell us anything. It explained what document classification systems can do, what they cannot do, and where professional judgement remains necessary — the last point being particularly important for a legal practice. We left with a much clearer sense of what one specific use case might be worth exploring.
April 2025 · Leadership Session
Case Studies
Detailed Engagement Outcomes
Three accounts of how engagements progressed from initial problem to operational result.
Invoice Late-Payment Prediction for a Kuala Lumpur Wholesaler
Challenge
The accounts receivable team was managing approximately 800 active accounts with no systematic way to predict which invoices were likely to run past 60 days. The process relied on individual collector experience and was inconsistent across the team.
Approach
Data Readiness Assessment confirmed three years of usable payment history. A twelve-week pilot produced a classification model trained on account payment patterns, invoice characteristics, and sector data. The model was designed to flag accounts, not to replace collector judgement.
Result
The model's flagged accounts matched actual late payments at a rate the team found actionable. Follow-up calls on flagged accounts were prioritised, and the average collection cycle shortened over the six months following deployment. The system runs without Cendana Tech's involvement.
Total engagement: MYR 3,450 (assessment + pilot) · Duration: 14 weeks
Board AI Briefing for a Selangor Family-Owned Conglomerate
Challenge
The board was receiving conflicting advice from technology vendors about AI investment. Some presentations described transformative results. Others were difficult to evaluate. The principals wanted a source of information they could trust not to have a sales objective.
Approach
A half-day Leadership Reading Session conducted at their Klang Valley headquarters. The session covered ML fundamentals in non-technical terms, three worked examples from comparable conglomerate structures, and a section on where to be cautious about vendor claims. Bilingual written summary produced in English and Bahasa Malaysia.
Result
The board identified one subsidiary — a logistics operation — where a Data Readiness Assessment was worth commissioning. That assessment subsequently confirmed the data conditions were adequate, and a pilot is currently being scoped. The session gave the board a framework to evaluate future vendor proposals independently.
Engagement: MYR 470 (Leadership Session) · Duration: Half day
Data Readiness Assessment for a Penang Hospital Group
Challenge
Management had identified patient flow forecasting as a potential use case for ML. Before commissioning a pilot, they wanted to know whether their patient management system data was in a condition to support it — there were known inconsistencies in how different departments entered records.
Approach
A Data Readiness Assessment covering five years of patient admission records across three facilities. The assessment examined completeness, consistency of coding, and the fitness of the data for the forecasting question being considered. PDPA implications were also reviewed.
Result
The assessment found the data was usable for two of the three facilities but not the third. The report named the specific issues at the third facility and proposed a twelve-month data improvement plan. The decision to proceed with a two-facility pilot was made with clear understanding of what it could and could not tell them.
Engagement: MYR 1,150 (Data Assessment) · Duration: 3 weeks
Our Track Record
Professional Credentials
4.7
Average client rating
47+
Engagements completed
7
Years in Cyberjaya
100%
Pilots with full handover
Reach Us
Contact Cendana Tech
Phone
+60 3-8312 6749Address
91, Jalan Cyber 11, 63000 Cyberjaya, Selangor
Working Hours
Monday – Friday: 9:00 AM – 6:00 PM
Saturday: 9:00 AM – 1:00 PM
See What Cendana Tech Can Do for Your Firm
The initial conversation costs nothing. Describe your data situation and the problem you have in mind, and we will give you an honest account of how — or whether — we can help.
Contact Cendana Tech