Our data science & analytics projects are built to answer one question: “What should we do next?” We connect your operational systems—ERP, CRM, billing, marketing, field apps—and turn scattered rows of data into clean models, dashboards and predictive signals that business teams can actually use in day-to-day decisions.
Whether you are a growing startup or an established enterprise, we help you move beyond basic reports and spreadsheets. Our approach combines modern data engineering, statistical modelling and AI to deliver forecasting, anomaly detection, customer analysis and profitability views that are tightly aligned with your KPIs, not just generic charts.
services : Data Engineering, BI, ML, Decision Intelligence
clients : Retail, Manufacturing, Education, BFSI & SaaS
region : India-first with global remote delivery
engagement model : Project, Retainer & Embedded data team
Most organisations already have data—but it lives in silos: accounting software, inventory systems, HR tools, Excel sheets and WhatsApp exports. Teams spend hours cleaning and merging files, only to get reports that are outdated as soon as they are emailed. The mandate for our data science & analytics practice is to connect these dots and make insights always available, always trustworthy.
We typically start with a data health check—understanding current systems, exports and constraints. Then we define a minimal but robust data architecture: where data will live, how it will flow and who can see what. This might mean a cloud data warehouse, or a well-structured SQL layer on your existing infrastructure, depending on your stage and budget.
Once the foundation is ready, we create a library of shared metrics: revenue, margin, ageing, churn, utilisation, yield, on-time delivery and more. These metrics feed into interactive dashboards and deep-dive reports that allow teams to slice by branch, segment, product, channel or salesperson. On top of this, we add machine learning where it truly matters—forecasting demand, scoring customers, predicting late payments or suggesting optimal stock levels.
For leadership teams, this translates into a single source of truth they can open every morning instead of waiting for manual Excel reports. For operations and finance, it means real-time visibility into bottlenecks and leaks. Over time, the organisation becomes more data-driven, with conversations shifting from “What happened?” to “What should we adjust next week, next month and next quarter?”—backed by SURENA’s data science & analytics stack.
