Artificial Intelligence

What is AI?

Artificial intelligence (AI) is the concept of compute engines showing cognitive abilities often associated with beings of intelligence. This is, the ability for reason, learning and self-correction and is often translated through tasks that require human participation, such as visual interpretation, language processing, decision making and predictive behaviour.

What we do

Lean Analysis

  • Data and Business Analysis
  • Data Quality Evaluation
  • Problem Identification and Breakdown
  • Hypothesis Creation

Lean Design

  • Data Model Design
  • Process Redesign for Automation and AI
  • Data Architecture
  • Solution Architecture
  • Enterprise Architecture


  • Stakeholder engagement to merge data and automation governance models for AI
  • Opportunity Assessment
  • Business Case Development
  • Technical Governance

What can AI do for your company?

Price Optimisation

Discover the ideal discount rate should be for a proposal to ensure that you’re most likely to win the deal by looking at specific features of each past deal that was won or lost.


Discover the ideal discount rate should be for a proposal to ensure that you’re most likely to win the deal by looking at specific features of each past deal that was won or lost.

Managing for Performance

Use dashboards to visually see which salespeople are likely to hit their quotas along with which outstanding deals stand a good chance of being closed.

Lead Scoring

Compile historical information about a client, along with social media postings and the customer interaction history and rank the opportunities or leads in the pipeline according to their chances of closing successfully.

Upselling and Cross-selling

Identify which of your existing clients are more likely to buy a better version of what they currently own (up-sell) and/or which are most likely to want a new product offering altogether (cross-sell).

Price Optimisation

Using AI to determine the optimal maintenance schedule for production equipment.


Using AI to predict what your customers are going to order. This reveals what supplies will be required and orders can be placed earlier, assuring priority.

Managing for Performance

Customer responsiveness is tracked by the AI which orders materials on a Just in Time basis. That means materials arrive precisely as the machines need it, so it doesn’t need to be warehoused and stored until demand catches up with supply.

Lead Scoring

AI can assist with getting product to customer in an expeditious manner. AI which is connected directly to your fleets, can re-route materials on-the-fly. It can also determine the most cost effective courier or delivery service available.

Upselling and Cross-selling

AI can use these algorithms to glean new insights from what was previously incomprehensible data. This can even be expanded to translating foreign languages.

Accounts Payable/Receivable Processing

Machine Learning can implement invoice coding behaviours, allocating and recommending where transactions should be coded.

Accounting Queries

Natural Language Processing can apply sentiment analysis in areas where high volumes of queries need to be prioritised such as Payroll and AP/AR (externally and internally).


Algorithms can be applied to detect fraud or duplication. All over the business, departments and divisions record transactions in journals, which need to be consolidated and reconciled. With the combination of RPA and Machine Learning gather and consolidate transactions and reconcile them in your ERP.


Machine Learning can assist in predictive analytics and forecasting. A mixture of regression methods and algorithms can be used for insights in demand/supply forecasts, network management, rostering and scheduling etc.

AI Chatbots

Providing access to real time customer, supplier and employee information. Chatbots are used to efficiently solve common questions or queries from customers including the latest account balances, when certain bills are due, the status on accounts and more.

Expense Management

With OCR capabilities, data can be extracted from receipts, audit expenses and alert humans when a possible infraction has occurred.

Validate Transactions & Cut Down on Approval Processes​

Can do this by comparing data from past purchases and looking at external force. AI and data analytics, can then effectively approve the deal.

Decision Intelligence​

Uses a sophisticated algorithm to examine how an account is used over time. Then, using all of the data that it has compiled, it detects normal and abnormal spending in real time.

Price Comparisons​

If you work with a number of suppliers to source a specific product with fluctuating prices, track changes and best pricing automatically with a robot. Robots can even sneak into the web code to extract catalogue pricing.

Market Intelligence

Vetting suppliers’ credentials on a periodic basis to ensure they meet your threshold is a highly manual task that’s easy to put off for another day. Charge a robot with this job, and it will deliver a full report on time, every time.

Answer Common Questions ​

Bots that can answer simple and oft-asked questions online, without the need for the customer to pick up the phone.

Handle Multiple Interactions​

Troubleshoot the minor issues or to get an update on their account system.

Field Calls​

Field calls away from the busy agents and then gather the data from the clients beforehand.

Predict Customer Behaviour​

AI is now helping to predict customer behaviour on the phone, to provide recommendations to the customer service reps on how best to deal with the issue.

Reduce Staff Training Costs​

Bot can serve the agents with related information; the agents won’t need high-level training to learn everything.

Medical Billing and Coding

Automatically recognise and extract data from medical documents for proper coding and billing.

The Merging of DataOps and MLOps

When it comes to building AI solutions, the most important items to focus on are the data and the deployment. In this video, Head of Data Science, Ben Lynton, unpacks both DataOps and MLOps, illustrates their differences, goals, and discusses how they can work together to streamline your end-to-end AI strategy.

Learn more about Natural Language Processing (NLP)

Does your organisation struggle to quickly access information? Find out how your employees and customers can find what they need in seconds with intelligent search (Amazon Kendra) and chatbots (Amazon Lex).

Moving to MLOps with AWS Sagemaker

MLOps, or Machine Learning Operations, are a set of best practices that enable simple, reliable model deployments and monitoring. MLOps can save you time, money, and allow for “closed loop” systems where models are constantly being updated as new data cascades through the process.