Some of our previous work

Global Bank, Singapore

The bank wanted to identify the Critical Data Elements (CDE) across their Risk data infrastructure so that they can implement a targeted remediation plan to improve the quality of the highest value data required for compliance and regulatory reporting.


Role we played

Developed an algorithms to identify Critical Data Elements across all Risk Data assets
Automated the identification script to make it repeatable so that the identification process becomes continuous and seamless.
Saved 6-8 weeks of Analysis time from each cycle of identification process translating into significant effort and dollar save across the entire Risk function.
As a by product identified range of data issue which enabled the client to put in a highly targeted remediation plan with well defined outcome.

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Value Delivered

Provided a practical methodology and solution to solve wide ranging data quality issues in a focussed approach.
Saved 1.5-2 months of Data Analysis effort per cycle which equates to roughly 1.5 FTE effort save per annum.

Time Spent 4 Months

Large multi brand Insurance Company, Auckland

Review of sales and performance reporting process to identify opportunities for automation, data quality improvements and enhancements of large number of legacy reports.


Role we played

Conducted a rapid review of the highly complex sales performance reporting process to create visibility of the end to end process and various touchpoints.
Identified 50+ data sources, 40+ data flows and traced 80 + steps involving 38 databases across the organisation.
Identified Number of automation opportunities to reduce complexity and reliance on legacy systems & EUC’s.
Developed prototype to replace the highly non responsive reports with intuitive and interactive dashboards.

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Value Delivered

Made optimization recommendations which translated into close to 100 man days of effort save from the performance reporting process.
Designed a high level target solution and the transitional architecture for a modern analytical platform.

Time Spent 3 weeks

Telecom provider and a Large Insurance Group

Design and build an analytical data store which will create a common information model across different data assets so that end user have faster access to data to build interactive reports, dashboards and analytical models.


Role we played

Designed the Target architecture of the Analytical Data Store and related components.
Designed the Logical and Physical Data Model
Created the transitional architecture and the solution delivery plan to integrate various components of the solutions.
Provided data engineering capability to stand up the infrastructure in a hybrid environment and create the data pipeline.

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Value Delivered

Played an important role in creating a highly valuable analytical asset which reduced the barrier between IT and Business. By making data easily available through self service tools increased the usability of the organisational data into day to day business decision making.

Time Spent 10-12 Weeks

Australia and NZ based Wealth Service Provider, Auckland

Develop Solutioning Design for a Hybrid data platform for optimizing Digital Analytics.


Role we played

Designed and architected a solution in AWS that addresses the current and future business needs fully.
Focussed on re-usability of existing components instead of leading them to an expensive upgrade path, which reduced the upfront investment significantly.
Made available number of accelerators which will make the data migration process much faster and more efficient.
Developed a Digital Analytics Use case library which formed the basis of the analytical backlog.

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Value Delivered

Filled a critical skills gap by bringing together a team of Data and Digital analytics expert. By using existing IT assets and re-using components delivered significant savings on infrastructure spend.

Time Spent 6 Weeks

Consumption, Innovation & Organization

We have been involved in number of  projects across Financial Services Industry, Transport and Logistics and Manufacturing industry to build working prototypes by giving legs to ideas. Our clients used our capability as an ‘on demand’ innovation hub to accelerate ideas that often got de-prioratized as a result of BAU workload or competing project demands. We provide a highly expert team and capability to create a parallel lane for organization to fast track their innovation with minimal upfront investments.

Some of the prototypes we have built are,

  • Highly intuitive and interactive dashboards (in Power BI & Tableau) to optimise sales & performance reporting, measuring operational efficiency and migrate Credit Risk reporting from legacy Data Visualization platform
  • Branch Optimisation Model
  • Tracking of Cargo movement and location intelligence using GPS and sensor data
  • Develop intelligence and alerts from machine logs and IOT sensors for preventative maintenance and extend asset utilization lifecycle.

Developed proof of concept to demonstrate the power of AI and Machine Learning and how it can change the game for organisations.

Proof Of Concept delivered:

  • Extraction of Financial and non financial information using OCR and NLP
  • Classification of Financial Information for Lending acceleration
  • Image recognition using Computer Vision to detect damages and breakage in industrial assets

We offer a fully managed ‘Insights as a service’ for organisations with low IT maturity. Under this model the client provides the data in a secured cloud hosted environment and we do everything else to deliver insights back to the client so that they can make decisions based on facts. This is a highly cost effective solution for organisation that have an appetite for data driven insights but lacks the IT or the people capability.

Data Engineering is emerging as a critical capability for many organisations wanting to get better with Data. However, building a Data Engineering team from ground up can be time consuming and expensive. Moreover with shortage of data engineering skills in the country finding the right person can prove challenging.

Our as a service model takes care of all the data engineering needs for our clients and help to build a robust and secured data infrastructure, manage the data pipeline and make data from various sources available to business without having to set up and maintain a big engineering team.

We offer a hybrid delivery model for building analytics capability whereby we make available highly skilled Data Modellers, Subject Matter Experts and Developers to help our clients build an extended analytics team which they can use for smoothing out seasonal spikes or for skills augmentation.

We manage the team on behalf of our clients and so that they can focus on managing the outcomes.

We offer this service both from New Zealand as well as from our offshore delivery centre based in India.

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