From pipelines to AI, we help you forecast better, reduce churn, and make faster decisions.

End-to-End
From ETL pipelines to BI dashboards and ML models.

Proven Impact
12% lower churn. 18% better forecasts. 80% less reporting time.

Industry Breadth
Energy, SaaS, Finance, E-commerce, Blockchain.

Fast Delivery
From discovery to delivery in weeks, not months.
Featured Case Studies

ENTSOG Transparency Dashboards (Energy/Utilities)
Problem:
ENTSOG needed to publish >5GB/day of gas data from European TSOs for 60,000+ stakeholders. Manual Excel-based workflows caused delays, errors, and unreliable forecasts.
Action:
- Designed and deployed Azure Data Factory pipelines to automate ingestion from APIs, databases, and XML files.
- Created star-schema data models with data quality checks (freshness, uniqueness, schema validation).
- Built real-time Power BI dashboards with filters for country, TSO, and indicator.
Result:
- +18% forecast accuracy for storage data.
- −40% XML rejects due to schema validation.
- −80% manual reporting effort through automation.
- Dashboards power the ENTSOG Transparency Platform, serving regulators and market participants daily.

SaaS Churn Prediction & Forecasting (Fintech SaaS)
Problem:
Recurring revenue growth was threatened by high churn and low forecast accuracy. Customer success teams worked reactively, and finance lacked reliable planning tools.
Action:
- Built Gradient Boosting + CNN churn models trained on user activity, payments, and support data.
- Delivered segmentation dashboards in Power BI for churn risk tracking.
- Integrated model outputs into CRM, enabling proactive outreach.
Result:
- 12% churn reduction across key cohorts.
- +14% forecast accuracy for revenue planning.
- +25% campaign CTR through targeted retention offers.

Executive BI Dashboards (Cybersecurity SaaS)
Problem:
Executives lacked consistent, real-time visibility into revenue, product usage, and adoption metrics. Reporting was manual, slow, and inconsistent.
Action:
- Designed star-schema models for revenue, product, and support data.
- Built executive-level Power BI dashboards for revenue KPIs, funnels, and retention cohorts.
- Partnered with product teams to embed dashboards into workflows.
Result:
- −80% reporting time for executives.
- +15% product adoption after identifying feature drop-offs.
- −30% incident resolution time through anomaly detection.

E-commerce Demand Forecasting (Retail)
Problem:
Forecast accuracy was stuck at 68%, leading to stockouts and costly overstock.
Action:
- Developed a hybrid CNN + LSTM + Attention model for weekly demand forecasting.
- Incorporated promotions, seasonality, and external signals into features.
- Delivered forecasts via dashboards for supply chain teams.
Result:
- Forecast accuracy improved from 68% → 91%.
- Reduced stockouts and excess holding costs.
- Increased customer satisfaction through improved product availability.

Customer Segmentation & Personalization (SaaS)
Problem:
Marketing campaigns were too generic, resulting in low engagement and high acquisition costs.
Action:
- Applied K-Means and Hierarchical clustering on purchase history, demographics, and engagement data.
- Identified 5 actionable personas integrated into marketing automation.
Result:
- +25% email CTR on segmented campaigns.
- −15% CPA, improving marketing ROI.
- Stronger personalization across customer journeys.

Ethereum Validator & Staking Analysis (Blockchain/Crypto)
Problem:
Post-Ethereum PoS merge, investors lacked transparency into validator exits, deposits, and reward sweeping patterns.
Action:
- Built SQL-based dashboards in Dune Analytics to map deposits, withdrawals, and validator activity.
- Clustered wallet addresses to reveal staking pools and centralized entities.
- Visualized liquidity flows and validator exits in real time.
Result:
- Provided actionable insights into validator concentration and risk.
- Supported investors and researchers in tracking staking flows.
- Boosted transparency in Ethereum’s staking ecosystem.
Industries We Serve
Energy & Utilities
Transparency reporting, demand forecasting, and grid-load optimization.
SaaS & Fintech
Churn prediction, revenue forecasting, and customer health tracking.
E-commerce
Customer segmentation, personalization, and demand forecasting.
Blockchain
Validator dashboards, staking analytics, and trading models.