Our Industries

Customer lifecycle and loyalty strategy across sales, service, and mobility services, designing data-driven growth strategies for vehicle sales, financing, maintenance, and accessories, defining analytics-driven use cases leveraging vehicle and mobility data.

Segmentations, vehicle sales performance, dealer analytics, and aftersales reporting, analyzing maintenance frequency, service utilization, and warranty claims, customer journey analytics (understanding end-to-end customer interactions from purchase to aftersales).

Repurchase & Upgrade Prediction (identifying customers likely to replace or upgrade their vehicles). Service & Maintenance Prediction (forecasting maintenance needs and service intervals), Churn & Brand Switching Prediction (detecting customers at risk of switching brands or dealers).

Integrating CRM, dealer systems, connected car platforms, and finance data via APIs, processing sensor and usage data at scale, enabling unified analytics across distributed dealer systems, commercial tool to opensource migration.

AI models for proactive servicing and reduced downtime, personalized vehicle & service recommendations, forecasting vehicle and spare parts demand.

Dealer Performance dashboards (sales, margin, and service KPIs by dealer), Customer Analytics dashboards (loyalty, lifecycle, and engagement views), Operational dashboards (monitoring service capacity and utilization).

Customer Loyalty Assessment (measuring customer loyalty, product stickiness, and lifetime value across retail and commercial banking), Portfolio Growth Strategy (optimizing acquisition, cross-sell, and wallet share using analytics, Risk & Profitability Strategy (balancing growth and risk through data-driven portfolio insights), Underwriting Decision Flows, Auto-limit Process Design, implementing and maintaining IFRS9-compliant processes to meet regulatory requirements.

Segmentations, Customer Behavior Analytics (analyzing product usage, engagement, and transaction behavior), Portfolio Performance Analytics (tracking credit, deposit, and fee income performance), Operational Analytic (monitoring process efficiency and service quality).

Credit Risk Modeling (predicting probability of default and loss metrics), Fraud Detection (identifying anomalous transactions and behaviors), Churn & Attrition Prediction (forecasting customer inactivity and exit risk), Expected Credit Loss (ECL) Calculations, Income Estimation, Collection Scorecards, Behavioral Scoring.

API-Based Data Integration (connecting core banking, CRM, and digital platforms via secure APIs), Regulatory Data Pipelines (Supporting auditable and compliant reporting), Real-Time Streaming Data (enabling instant fraud and decisioning use cases), Commercial tool to Opensource Migration.

Automated Credit Decisioning (AI-driven approval and limit assignment, Fraud Scoring Engines (real-time transaction risk scoring), Personal Finance AI (personalized financial recommendations).

Risk dashboards (monitoring credit and fraud exposure), Executive dashboards (growth, profitability, and loyalty views), Regulatory Reporting Views (transparent compliance dashboards).

Customer loyalty assessment, conversion optimization, and marketplace strategy.

Segmentations, funnel analysis, campaign feasibility, optimization and tracking, and behavioral analytics.

Churn prediction, Likelihood to purchase modeling, CLV forecasting, and promotion effectiveness modeling.

API-based integration of clickstream, payment, logistics, and CRM data, commercial tool to opensource migration.

Recommendation engines, dynamic pricing, and fraud detection.

Growth dashboards (conversion, revenue, and acquisition performance), Customer Segmentation dashboards (behavioral and value-based segment views), Marketing Performance dashboards (campaign and channel effectiveness).

Customer loyalty assessment, consumption optimization, and sustainability analytics.

Segmentations, consumption patterns, billing insights, and operational reporting, route optimization.

NPS Modeling, demand forecasting, churn prediction, outage risk modeling, and loss detection, fraud detection.

Smart meter, IoT, and enterprise system integration using API, commercial tool to opensource migration.

Load forecasting, anomaly detection, and optimization AI.

Consumption, operations, and risk dashboards.

Subscriber loyalty assessment, content strategy, and monetization optimization.

Segmentations, viewing behavior, content performance, and engagement analytics.

Churn prediction, content recommendation, and demand forecasting.

Streaming, CRM, and platform data integration via APIs, commercial tool to opensource migration.

Recommendation systems, personalization, and content optimization AI.

Subscriber, content, and revenue dashboards.

Policyholder loyalty assessment, retention strategy, and product optimization, evaluating renewal behavior, cross-sell potential, and loyalty drivers, optimizing underwriting, pricing, and claims performance.

Segmentations, monitoring claims frequency, severity, and settlement times, underwriting performance, and customer behavior insights, tracking premium, loss ratio, and renewal KPIs, analyzing coverage gaps and engagement.

Churn prediction claims risk modeling, and customer lifetime value estimation, forecasting claim costs and reserves, identifying suspicious claims and behaviors (fraud detection modeling), predicting non-renewal and lapse risk.

Integration of policy, claims, CRM, and partner data through APIs, external data enrichment, supporting advanced analytics workloads, commercial tool to opensource migration.

AI-based fraud detection, pricing optimization, and intelligent underwriting.

Underwriting dashboards (risk and pricing performance views), Customer Analytics dashboards (loyalty, lifecycle, and engagement views), Claims dashboards (operational and financial tracking), Executive Profitability Views (portfolio-level insights).

Customer Loyalty Assessment (measuring loyalty, repeat behavior, and lifetime value across channels), Omnichannel Growth Strategy (aligning online and offline experiences using analytics), Assortment & Pricing Strategy (data-driven category and pricing optimization).

Sales & Margin Analytics (tracking performance by store and SKU), Inventory Analytics (monitoring stock turns and availability), Campaign Performance Analytics (measuring promotion effectiveness), Customer, Store, SKU segmentations.

Demand Forecasting (predicting sales at granular SKU levels), Churn & Inactivity Modeling (identifying disengaged customers), Promotion Uplift Modeling (estimating incremental campaign impact).

API-Based Data Integration (connecting POS, e-commerce, and loyalty systems via APIs), Supply Chain Data Pipelines (end-to-end inventory and logistics visibility), Real-Time Data Feeds (supporting rapid operational decisions), commercial tool to opensource migration.

Recommendation Engines (personalized product suggestions), Dynamic Pricing Models (AI-driven price optimization), Demand Optimization AI (automated replenishment decisions).

Store Performance dashboards (sales and margin monitoring), Category dashboards (assortment and pricing insights), Executive Retail Cockpits (business-wide performance views), Customer Analytics dashboards (Segment-level insights for marketing and retention teams).

Donor loyalty assessment, fundraising strategy, and impact measurement frameworks.

Segmentations, donation trends, campaign performance, and engagement analytics.

Donor churn, lifetime value, and campaign response modeling.

Integration of donor, campaign, and external datasets via APIs, commercial tool to opensource migration.

Donor targeting, personalization, and fundraising optimization AI.

Impact, fundraising, and engagement dashboards.

Customer value management (CVM) strategy, loyalty assessment, and lifecycle optimization across prepaid, postpaid and digital channels, designing data-driven retention, upsell, and cross-sell roadmaps based on churn and value insights, translating network investments into revenue growth and improved customer experience.

Segmentations, subscriber behavior analysis, analyzing voice, data, and digital usage to identify revenue and engagement drivers, monitoring churn, tenure, reactivation, and loyalty metrics across segments, campaign feasibility and optimization, campaign performance tracking, network usage insights.

Churn prediction, upsell propensity, winback propensity, next-best-action, timeseries forecasting models and best device recommendation.

API-based integration of CRM, billing, network, digital data into scalable analytics platforms, processing high-volume telecom data with robust data pipelines, enabling near real-time analytics for customer actions and operations, commercial tool to opensource migration.

Social network analysis, Real-time decision engines, fraud detection, personalization, AI-driven next-best-offer and tariff recommendations, process mining and model performance monitoring.

Executive dashboards (High-level views of revenue, churn, and loyalty KPIs), Operational Monitoring dashboards (Real-time tracking of service and network quality), Customer Analytics dashboards (Segment-level insights for marketing and retention teams).