AI Driven Consulting

Boost your digital transformation with the power of AI driven Lean solutions and IT quality services

As the global economy is becoming more digital, customer data is increasing and machine learning technologies are perfectly poised to unlock its value.

Machine Learning improve in proximity targeting, marketing profiling, prevent churn, and increase MROI

Improving the ROI dollars spent by optimizing marketing campaigns

Reducing churn by looking at the evolution of the customer's profiles

Forecasting LTV to improve marketing budget forecasting

Customer segmentation

Our algorithms based on sub-group discovery are very effective at spotting small groups of customers that behave in a similar fashion. Successful Customer segmentation is paramount to reducing MROI through targeted actions.

Customer churn prediction

Using a historical dataset of customers who churned in the past and discovering patterns within this data, we can forecast  the current customers that have a high probability of churning.  Marketers are therefore enabled to implement churn preventive actions that also improve MROI.

Customer lifetime value forecasting

Our machine learning systems are an excellent way to predict the LTV of existing customers. Business forecasts and growth prediction often rely on  LTV.  As these forecasts  drive marketing spending, good LTV prediction is a key reducing costs.


Customer pricing segmentation, loss ratio modelling using big data analytics

Since 2015 we have been doing hands on ML  for the insurance sector, starting with bespoke 6-8 weeks data science  training courses for your analytics team.  Our approach favors improving an existing process rather than disrupting it via ML or AI bricks.

Our full offering of solutions covers:

Fraud Detection


Churn prevention

Claims automation

Mix Change Analysis

Business use: identify small and large segments of customers with higher than average increase or decrease in volumes, and eventually bad expected loss ratio levels

Inputs: New business quotes data on two different periods of time, before and after the tariff change

Outputs: Segments presenting high risk of adverse selection (New Business)

Tools: Proprietary local exploration tool (Bottom-up approach)

Market Prediction

Goal: Improve product pricing by reverse engineering competition prices for P&C insurance

Business use: Outbid competitors in real-time and increase market share

Inputs: Customers data + Brokers data

Outputs: Competitive index

From Probabilities to Action

Goal: Decrease churn rate or increase conversion rate through action

Business use: Generate concrete targeted actions based on the existing churn or conversion model

Inputs: Customers data and churn/conversion model

Outputs: Specific marketing action

Tools: Proprietary prescription tool

Fraud Detection

Goal: Improve the performance of a fraud detection team through ML across all insurance lines

Business use: Improve on an existing time-testd business rules approach

Inputs: Customers data + Claims data + Graph theory

Outputs: Enhanced Fraud Score

Hadrian AI Research

Extensive NLP (Natural Language Processing) work for contract processing, claims processing and document classification.

Proprietary affinity matching for HR agencies

Proprietary affinity matching engine for HR agencies to find the perfect fit between candidates and job openings using MBTI type questionnaires, Resumes and job openings via NLP and machine learning.

Voice analysis for support centers

Voice analysis for support centers to improve customer experience and reduce time to handle. Voice pitch-based fraud detection model.

Data-Science Accelerator

Custom Online and on-premise Data-Science Accelerator program covering all aspects of machine learning for Insurance and Finance (data pipeline and Algorithmic Trading).

We can help you make better business predictions