Data Science & AI

Harness the power of machine learning to build predictive insights for your business.

We are a team of data engineers, AI consultants, software developers and experienced business leaders here to transform your data into actionable insights,
so you can make better business decisions.

We provide a complete business overview (descriptive), what-if insights (predictive) and intelligent recommendations (prescriptive).

Why data science is important?

Without data analytics, companies are blind and deaf, wandering onto the web like a deer on a freeway.

- Geoffrey Moore, Management Consultant, Author

The Business Impact of Data Science


79% of companies that uses AI have reduced their cost.*


67% of companies that uses AI reported increase in revenue.*

How Data Science can help your business?

Get insightful information about your organisation at your fingertips

Cross-reference external data against yours for better benchmarking and opportunities to capture (big data)

Sense-make insights with presentable and interactive data visualisation

Get predictions and what-if scenarios based on parameter changes (financials, inventory etc.)

Get prescriptive insights from AI on how to optimise operational efficiency, reduce costs, increase customer engagement and revenue.

*Source: Mckinsey & Company global survey on AI in 2021.

Types of data analytics

Descriptive Data

Provide analytics based on current and historical data efficiently.

Predictive Data

Use machine learning and statistical data modelling to make predictions on future outcomes.

Prescriptive Data

Use AI to generate insightful recommendations to drive better decision-making.

Data Science Industry Solutions

Big data analytics

Transactions processing systems

Customer databases

Financial markets data

Network & server logs

IOT & sensor data

Traffic & weather

Finance analytics

Cashflow prediction

KPIs & ratios monitoring

Accounting apps integration

Budget prescription

Risk predictions

Retail analytics

Recommendation engine

Price optimisation

Customer segmenting & profiling

Customer sentiment analysis

Churn analysis

Manufacturing analytics

Predictive maintenance

Real-time quality monitoring

Anomaly detection

Maintenance scheduling

Process optimisation

Supplies analytics

Demand forecasting

Inventory optimisation

Early warning systems

Supplier performance

Freight costs optimisation

HR analytics

Employee attrition

Salary analysis


Stress indicators

Recruitment & sourcing

Case study: Aviation

Predicting jet engine faults for the world's biggest engine maker.

Performing fault diagnostics of high-value engineering systems such as jet engines is critical to detect hidden problems within the underlying system. As such we were commissioned to use data science to capture all relevant data sources, process them and provide useful analytics that would be able to prevent costly failures and cost-effective scheduling of maintenance cycles.

What we did

Developed an enterprise dashboard for staff to monitor & predict jet engine faults.

Onboarded jet engine performance, parts stocks and real-time sensor data for processing using machine-learning.

Utilised AI to perform predictive analytics.