Client satisfaction and trust

What Our Clients Say

Experiences from organisations who have worked with us across OCR, supply chain, and conversational search projects.

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Client Reviews

WC

Wei Cheng Tan

Head of Operations, Singapore

We brought Helioquant in to help digitise about 15 years of archived warehouse records. The OCR system they built handled everything from faded receipts to handwritten inventory notes. The accuracy was noticeably better than the generic tools we had tried before, and the integration with our document management system was seamless.

25 January 2026

SB

Siti Balqis Rahman

Procurement Manager, Singapore

The supply chain AI solution has been a practical addition to our planning workflow. Forecasting accuracy improved noticeably in the first quarter after deployment. My only note would be that the initial data integration phase took a bit longer than expected, but the team communicated the delays clearly and the end result was solid.

18 January 2026

KP

Kumar Patel

IT Director, Singapore

We deployed a conversational search interface for our internal knowledge base. Staff adoption was much faster than we anticipated — people just started asking questions naturally. The Helioquant team was thorough with documentation and training, which made the transition easy for our support staff.

2 February 2026

ML

Michelle Loh

Compliance Officer, Singapore

Data security was our primary concern when looking for an AI partner. Helioquant took our compliance requirements seriously from the very first meeting. They worked within our infrastructure, respected our access policies, and produced thorough audit documentation. The OCR solution they delivered met both our accuracy and our compliance needs.

30 January 2026

JW

Jason Wong

Supply Chain Lead, Singapore

What I appreciated most was the honesty during the scoping phase. Helioquant told us upfront which parts of our supply chain data would yield strong predictions and which areas needed cleaner inputs first. That kind of candour saved us from wasting time on unrealistic expectations. The models they deployed are now part of our weekly planning routine.

8 February 2026

AL

Aisha Lee

Customer Experience Manager, Singapore

The conversational search tool Helioquant built for our customer portal reduced the volume of basic support tickets within weeks of going live. Customers seem to genuinely prefer asking questions in their own words rather than trying to guess keywords. The analytics dashboard also helps us identify gaps in our documentation.

11 February 2026

Client Success Stories

Case Study — OCR

Digitising a Government Agency's Legacy Records

Challenge

A Singapore government agency needed to digitise over 200,000 archived documents spanning three decades. Many were degraded, contained handwritten annotations in multiple languages, and used non-standard form layouts that commercial OCR tools could not handle reliably.

Solution

Helioquant developed a custom OCR pipeline trained on 5,000 representative document samples. We built pre-processing steps for image enhancement, a multi-model architecture for printed and handwritten text, and post-processing rules for agency-specific formatting. The pipeline integrated directly into their existing records management system.

Results

Character-level accuracy reached 96.3% across the full document set, compared to 71% from the previous off-the-shelf tool. Processing time was reduced from an estimated 18 months of manual work to 11 weeks of automated processing with human review on flagged items. The project was completed within the agreed timeline and budget.

Case Study — Supply Chain AI

Improving Demand Forecasting for a Regional Distributor

Challenge

A distributor operating across Singapore and Malaysia was experiencing frequent stockouts on key products while simultaneously carrying excess inventory on slower-moving items. Their existing demand planning relied on spreadsheet-based forecasts that did not account for seasonal patterns or external market signals.

Solution

We integrated three years of sales data with external signals including weather patterns, public holidays, and regional economic indicators. A gradient boosting model was trained to produce weekly demand forecasts by SKU and location, with confidence intervals that helped the planning team make informed decisions about safety stock levels.

Results

Forecast accuracy improved by 28% within the first quarter. Stockout incidents dropped by 35%, and excess inventory carrying costs decreased by approximately 18%. The planning team now uses the AI recommendations as a starting point for their weekly reviews rather than building forecasts from scratch.

Case Study — Conversational Search

Reducing Support Ticket Volume Through Natural Search

Challenge

A financial services firm had an extensive knowledge base but found that customers rarely used it effectively. Keyword search returned too many irrelevant results, leading customers to submit support tickets for questions that were already answered in the documentation.

Solution

Helioquant built a conversational search interface that allowed customers to ask questions in natural language. The system maintained dialogue context across follow-up questions, progressively narrowing results. We indexed over 3,000 knowledge base articles and trained the retrieval model on 12 months of actual support ticket data to understand real customer language patterns.

Results

Within eight weeks of launch, support ticket volume for documentation-answerable questions decreased by 41%. Customer satisfaction scores for the self-service portal increased from 3.2 to 4.1 out of 5. The analytics dashboard also identified 47 documentation gaps that the content team subsequently addressed.

Get in Touch

Address

182 Cecil Street, #17-01
Frasers Tower, SG 069547

Hours

Mon–Fri: 9 AM – 6 PM
Sat–Sun: Closed

By the Numbers

6+

Years of Experience

80+

Projects Delivered

4.7

Average Client Rating

94%

Client Retention

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