Client Feedback
What Our Clients Have to Say
The work speaks through the experiences of the organisations we serve. Here are some of their stories.
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Client Testimonials
Dr. Chen Ting
Research Scientist, Singapore
Vernicle helped us build a classification pipeline for our genomic variant data that significantly reduced the manual review burden on our team. What I appreciated most was their insistence on proper validation — they pushed back when we wanted to rush, and the final model was stronger for it. The documentation they left behind means our postdocs can maintain and retrain the model independently.
25 January 2026
Priya Subramaniam
VP Engineering, Singapore
Our NOC was drowning in alerts — over 2,000 per day, most of them noise. Vernicle's alerting system brought that down to around 180 actionable items. The team spent time understanding our infrastructure before building anything, which meant the model actually knew the difference between a routine fluctuation and something worth escalating.
1 February 2026
Marcus Koh
Facilities Director, Singapore
The digital twin Vernicle built for our commercial building portfolio has changed how we approach maintenance planning. We can now test scenarios before committing resources. The initial build took longer than I expected — about four months — but the calibration process was thorough and the end result justified the timeline.
8 February 2026
Dr. Jennifer Low
Head of Bioinformatics, Singapore
We engaged Vernicle for microscopy image segmentation and were impressed by how quickly they grasped the biological context. They did not just apply off-the-shelf models — they adapted the architecture to our specific cell types and staining protocols. The accuracy improvement over our previous approach was meaningful.
18 January 2026
Ahmad Tan
SRE Team Lead, Singapore
Good engagement overall. The alerting model integrates well with our Prometheus and PagerDuty stack. I would have liked slightly more flexibility in the configuration interface, but the core logic is solid and the alert noise reduction has been noticeable. Their team is responsive and straightforward to work with.
3 February 2026
Sarah Wong
Urban Planning Analyst, Singapore
Vernicle helped our department build a simulation model for pedestrian flow in a new transit development. Their approach was methodical — they started with historical data, calibrated carefully, and only then layered in predictive features. The scenario testing tool they delivered is now part of our standard planning workflow.
30 January 2026
Case Studies
Success Stories
Case Study — Biological Data
Protein Structure Prediction for a Biotech Startup
The Challenge
A Singapore-based biotech firm needed to screen a library of 12,000 protein variants for binding affinity but lacked the computational infrastructure to process them within their grant timeline.
Our Approach
We developed a transfer-learned model using existing crystallography data, then fine-tuned it on the client's proprietary assay results. The pipeline processed candidates in batches, flagging high-probability hits for experimental validation.
The Outcome
Screening time reduced by approximately 70%. The model identified 34 high-confidence candidates, 28 of which were confirmed by the lab. The client met their grant deadline with three weeks to spare.
Case Study — Intelligent Alerting
Alert Noise Reduction for a Regional Cloud Provider
The Challenge
A cloud hosting company's operations team was receiving over 2,400 alerts daily across their infrastructure, leading to fatigue and missed critical events. On-call engineers reported significant stress and response delays.
Our Approach
We conducted a six-week alert audit, built correlation models across their monitoring streams, and developed a prioritisation layer that learned from historical incident resolution data. Integration with PagerDuty was handled as part of the delivery.
The Outcome
Daily alert volume dropped to roughly 200 actionable items — a 92% reduction. Mean time to response for genuine incidents improved by 40%. The on-call team reported markedly lower stress levels within the first month.
Case Study — Digital Twin
Energy Optimisation for a Commercial Building Portfolio
The Challenge
A property management firm operating six commercial buildings in the CBD wanted to reduce energy costs without compromising tenant comfort. Manual adjustments to HVAC schedules were time-consuming and inconsistent.
Our Approach
We built digital twins of each building incorporating occupancy sensors, weather data, and BMS feeds. Predictive models enabled scenario testing for different HVAC configurations, with a dashboard for the facilities team to run simulations.
The Outcome
Energy consumption across the portfolio decreased by approximately 15% in the first quarter. The scenario testing tool became a standard part of the quarterly planning process, and tenant comfort scores remained stable throughout.
Trust & Credentials
By the Numbers
8+
Years in Operation
45+
Organisations Served
4.8
Average Rating
72%
Returning Clients
Get in Touch
Contact Information
Phone
+65 9618 4273Address
30 Raffles Place,
#19-08, Singapore 048622
Hours
Mon–Fri: 9 AM – 6 PM
Sat: 10 AM – 2 PM
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