Strategy & Execution
Data Science
We help businesses become data-led organisations through data strategy, technology builds, machine learning and AI services. Our structured problem-solving combined with deep analytics and cloud engineering capabilities enables rapid delivery of measurable value. We work across platforms, specialising in AWS and Azure, and run productionised Machine Learning through our ML Platform with EngageIQ as the execution layer.
Data-centric AI for enterprises that is practical, productionised and measurable
Features you'll love
ML & Predictive
Modelling
We build and deploy ML models - from churn and propensity to pricing and fraud detection - to predict customer actions and protect bottom-line margin.
Personalisation
Engines
Powered by EngageIQ, our personalisation engines plug into your existing LMS and CRM to match the right offer to the right customer in real time.
Marketing Mix & ROMI Modelling
We model marketing-mix performance and channel attribution to optimise your spend allocation and ensure every marketing rand works harder.
AI & Generative AI Solutions
We replace slow, intensive legacy processes with agentic workflows, document AI, and custom knowledge assistants built on LangGraph and MCP architectures.
ML Platform
(IMLP)
Our AWS-native platform manages the end-to-end machine learning lifecycle - from feature stores to automated deployment, versioning, and drift monitoring.
Data Strategy & Architecture
We architect cloud-native environments, single-view customer data layers, and analytics lake-houses built for enterprise scale and governance.
Want to know more? Let us help.
Client Impact
Multinational Institution
Analytics automation with GenAI
Challenge
A machine learning model required manual, multi-step implementation. High demand for outputs meant the process was not scalable.
Solution
Databricks workflows, FastAPI backend, React frontend for self-service requests, automated PPTX generation and ClaudeSonnet for commentary generation.
Result
850+ high-quality insights delivered. Cycle time reduced from days to minutes.
Large Insurer
Leads prioritisation
Challenge
Sales team had a large pool of leads but no way to prioritise those most likely to convert, resulting in wasted effort.
Solution
ML propensity model built on enriched customer data to score and rank leads by conversion likelihood, with ongoing recalibration.
Result
238% improvement in conversion in first period.
71%
overall improvement.
Retailer
Lapsed-customer re-activation
Challenge
Large base of lapsed customers was not being effectively targeted. Generic outreach had failed to re-engage them.
Solution
ENS data enrichment combined with ML-driven targeting to identify and engage the most re-activatable lapsed customer segments.
Result
Transaction volumes +124%.
Sales value +167%.
Gross profit +187%.
Ready for Eighty20 to help you too?
Client References
We are pleased to recommend Eighty20 as a trusted partner for data science and technology enablement. Several ML models have been operationalised with measurable value, including significant improvements in conversion rates.
Senior Executive, Data Insights, Assupol
Their technical expertise combined with an agile, pragmatic and solution-oriented approach enabled us to deliver significant value back into the organisation within a short period of time.
Head of Data Science, HomeChoice
