– WHAT WE DO
Everything we build
starts with your problem.
Not a package. Not a template. We identify which service gives the highest return first — then build it. No lock-ins before you’ve seen results.
We go into your raw data and find the patterns, correlations, and anomalies that explain your business performance. Statistically validated, decision-ready.
What the work involves
— Exploratory Data Analysis — ifull audit of your data, quality assessment, and what it can actually answer.
— Cohort & Segmentation Analysis — group customers or events by behaviour, not demographics.
— Correlation & Regression Modelling — find what is actually driving your key metrics, not just what correlates.
— Pricing & Elasticity Analysis — quantify how customers respond to price changes across segments.
— Statistical Hypothesis Testing — validate assumptions before making business decisions based on them.
Dedicated forecasting models for revenue, demand, and inventory — trained on your seasonal patterns, promotions, and external signals. Not generic models applied to your data.
What the work involves
— Revenue & Sales Forecasting — weekly, monthly, quarterly predictions with confidence intervals.
— Inventory Demand Planning — SKU-level forecasting accounting for seasonality and promotions.
— Seasonal Decomposition — isolate trend, seasonality, and residual components in your data.
— Changepoint Detection — identify structural breaks and unexpected shifts in your metrics automatically.
— Forecast Monitoring — automated accuracy tracking and retraining when performance degrades.
Predictive models trained on your specific business data — not generic templates. Classification, regression, and clustering problems. Built for production, not demos.
What the work involves
— Model Deployment & MLOps — production pipelines with drift detection and automated retraining.
— At-Risk Customer Identification — identify at-risk customers before they leave, with enough time to act
— Lead Scoring — rank inbound leads by conversion probability using behavioural signals.
— Recommendation Engines — collaborative and content-based filtering for product or content suggestions.
— Fraud & Risk Detection — real-time anomaly models that catch issues before they become losses.
Dashboards your team actually opens every morning. Built around your specific KPIs — not a generic template. We work in Power BI, Tableau, Looker, or Metabase depending on your stack.
What the work involves
— KPI Design & Data Modelling — define the exact metrics that connect to business outcomes.
— Multi-source Integration — connect and unify CRM, ERP, marketing, and finance data
— Documentation & Handover — full technical docs so your team can maintain and extend it.
05
AI Systems
&
Agents
-> Intelligent systems that work while you sleep
Production-ready AI systems trained on your data, your language, and your business rules. Not ChatGPT wrappers. Not demos. Systems your customers and team actually interact with every day.
What the work involves
— Custom (RAG) Knowledge Bot — answers questions from your documents, SOPs, and catalogues. Your data, not the internet.
— Voice AI Agents — inbound call handling in your customer’s language and dialect. Low latency, trained on your domain.
— AI Customer Support — resolves majority of queries without a human. Escalates intelligently when needed.
— Document Intelligence — extracts, classifies, and routes information from invoices, contracts, and forms automatically.
06
Synthetic
Data Generation
-> Real-quality data without real-data risks
When real data is scarce, sensitive, or too small to train on — we generate statistically identical synthetic data. Used by US and EU companies to train models without touching GDPR-protected data. Almost no boutique agency offers this.
What the work involves
— Tabular Synthetic Data — generate realistic transaction, customer, and operational datasets for model training
— Privacy Preservation — synthetic data that is statistically valid but contains zero real personal information
— Data Augmentation — expand small datasets to improve model accuracy without more real-world collection
— Rare Event Simulation — generate examples of rare cases (fraud, failures, edge cases) that don’t appear enough in real data.
— Distribution Validation — statistical tests to verify synthetic data matches real data characteristics.
07
ETL
Pipeline
-> Intelligent systems that work while you sleep
pipelines that pull data from every source, clean it, transform it, and deliver it automatically.
What the work involves
— ETL Pipeline Development — extract, transform, load pipelines connecting all your data sources into one clean system.
— Data Warehouse Setup — centralised, queryable data store built for your reporting and analytics needs.
— Multi-source Unification— Shopify, CRM, Google Ads, finance, ops — all merged into one reliable feed.
— Data Quality Monitoring — automated checks that flag missing or anomalous data before it reaches your team.
— Pipeline Maintenance — ongoing monitoring and fixes when source systems change, break, or add new fields.
08
Synthetic
Data Generation
-> Real-quality data without real-data risks
When real data is scarce, sensitive, or too small to train on — we generate statistically identical synthetic data. Used by US and EU companies to train models without touching GDPR-protected data. Almost no boutique agency offers this.
What the work involves
— Tabular Synthetic Data — generate realistic transaction, customer, and operational datasets for model training
— Privacy Preservation — synthetic data that is statistically valid but contains zero real personal information
— Data Augmentation — expand small datasets to improve model accuracy without more real-world collection
— Rare Event Simulation — generate examples of rare cases (fraud, failures, edge cases) that don’t appear enough in real data.
— Distribution Validation — statistical tests to verify synthetic data matches real data characteristics.
Not sure where to start
Tell us the problem.
We’ll find the right fit.
Most clients come to us not knowing which service they need — just knowing something in their business isn’t working the way it should. That’s exactly the right place to start. We’ve worked across 9 industries and 24 clients. If we’ve seen your problem before, we’ll tell you what fixed it. If we haven’t, we’ll tell you that too.