— Client voices
What our clients
say about working with us
Honest feedback from organisations who've worked through AI projects with us.
← Back to Home— Client reviews
From people who've worked with us
Agnes Yung
Head of Customer Experience, Retail — Hong Kong
We wanted to understand how our customers genuinely felt after service interactions — not just survey scores. Pulsemind built a sentiment analysis platform that processes feedback across WhatsApp, email, and our review channels. The dashboards are clear and my team actually uses them weekly. The setup was handled entirely on their end.
January 2026
Brian Lau
Operations Director, Logistics Firm — Kowloon
The forecasting model has been running for about five months now. Our demand estimates are considerably more accurate than what we were doing with spreadsheets. The sixty-day calibration window was something I didn't expect to matter much — it actually made a noticeable difference to the model's reliability in our specific context.
December 2025
Stephanie Chan
Knowledge Manager, Professional Services — Central
We had years of internal documentation that nobody could find or navigate effectively. Pulsemind structured it and built a knowledge base our team can query in plain language — in English and Traditional Chinese. New staff onboarding has improved noticeably. The team was thorough and the documentation they provided is genuinely useful.
January 2026
Kevin Tam
Finance Manager, Asset Management — Wanchai
I appreciated how candid they were in the discovery phase. They reviewed our data and told us clearly what it could support — including one area where they said a model wouldn't be reliable given the history we had. That kind of honesty made me much more confident in the parts of the project that did move forward.
November 2025
Rachel Leung
HR Director, Technology Company — Quarry Bay
We used the sentiment analysis platform to monitor internal employee feedback across a period of significant organisational change. It gave us a way to track mood shifts across departments without requiring people to put their names to specific comments. The fortnightly summary reports were well structured and actionable.
December 2025
Michael Wong
COO, Healthcare Services Group — New Territories
The knowledge base project was more complex than we initially anticipated — our documentation was in several languages and varying formats. Pulsemind worked through the complexity without making us feel it was a problem. The resulting system is something our team uses every day. We've continued with a maintenance arrangement since delivery.
January 2026
— In more depth
Selected case studies
Case study 01 — Sentiment Analysis
Retail chain — understanding post-purchase sentiment across 12 stores
Challenge
A mid-size retail chain in Hong Kong was collecting feedback through multiple channels — online reviews, post-purchase surveys, and in-store comment forms — but had no way to synthesise the data or detect patterns across locations. The volume of text made manual review impractical.
Solution
Pulsemind built a sentiment analysis pipeline that ingested and processed feedback from all three channels in near-real-time. A visual dashboard allowed management to filter by store, time period, and topic category. Monthly summary reports were generated and distributed automatically.
Results
Within two months of launch, the team identified a consistent service issue at three locations that had not been flagged through previous manual reviews. The client attributed a reduction in negative reviews of approximately 30% over the following quarter to changes made based on platform findings. Duration: 5 weeks.
The platform surfaced something we'd been missing for months. It wasn't complicated to use — it just worked the way our team needed it to.
Case study 02 — Forecasting
Logistics firm — demand forecasting for seasonal resource allocation
Challenge
A logistics company handling cross-border freight between Hong Kong and Greater Bay Area destinations was struggling with resource allocation during peak periods. Their planning relied on manager intuition and simple trend extrapolation, resulting in frequent over- and under-staffing.
Solution
Pulsemind reviewed four years of historical shipment data alongside external signals including public holidays and seasonal retail patterns. A machine learning forecasting model was trained and validated, with outputs presented as weekly demand estimates with confidence intervals at three planning horizons.
Results
During the sixty-day calibration period, the model's estimates were within 8% of actual demand in 14 of 16 measured weeks. The operations team reported more confident staffing decisions and reduced last-minute contractor costs in the two quarters following delivery. Total engagement duration: 3.5 months.
Case study 03 — Knowledge Base
Professional services firm — internal knowledge access for a 200-person team
Challenge
A professional services firm with offices across Hong Kong had accumulated substantial internal knowledge across a decade of operation — in document management systems, SharePoint folders, email archives, and local drives. New staff struggled to locate relevant precedents and procedures.
Solution
Pulsemind conducted a content audit, structured and indexed the accessible corpus, and built a retrieval-augmented generation system that allowed staff to query documents using natural language questions in both English and Traditional Chinese. The interface was integrated into their existing intranet.
Results
Within six weeks of launch, the firm reported a measurable reduction in internal information requests to senior staff — an issue that had been a consistent time cost. New staff onboarding time for document familiarisation was also reduced. The system has been in continuous use for eight months since delivery.
— By the numbers
Track record
6+
Years in operation
80+
Projects delivered
4.8
Average client rating
93%
Client retention rate
Phone
+852 6185 4392Working Hours
Mon–Fri: 9:00 AM – 6:30 PM
Sat: 10:00 AM – 2:00 PM
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