Predictive Analytics

Predictive analytics moves your organisation from reactive to proactive. Alchemilla Ventures builds sophisticated predictive models that forecast trends, anticipate customer behaviour, and optimise operations — serving clients.

Beyond Business Intelligence

While traditional BI tells you what happened, predictive analytics tells you what will happen — and prescriptive analytics tells you what to do about it. We combine statistical modelling, machine learning, and domain expertise to deliver forecasts your business can trust and act upon.

Our Predictive Analytics Offerings

• Demand Forecasting: Predict product demand across SKUs, regions, and time horizons. Essential for inventory management in retail and FMCG sectors. We build models using XGBoost, LightGBM, and temporal fusion transformers that adapt to seasonality and market trends unique to and the entire markets.

• Customer Churn Prediction: Identify at-risk customers before they leave. Our models analyse behavioural patterns, support tickets, and usage data to flag churn risks and recommend retention actions. Proven to reduce churn by 25–40% for SaaS and telecom companies.

• Financial Forecasting: Revenue projections, expense forecasting, and cash flow modelling for CFOs. We integrate macroeconomic indicators relevant to the the countryn economy — inflation rates, policy changes, and monsoon patterns — into our forecasting pipelines.

• Predictive Maintenance: Forecast equipment failures before they happen. Using IoT sensor data and historical maintenance logs, we help manufacturing plants ‘s industrial belt reduce downtime by up to 35%. Supports SCADA and PLC data integration.

• Risk Modelling & Fraud Detection: Credit risk scoring, insurance underwriting models, and real-time fraud detection for banks and NBFCs. Our models comply with guidelines and incorporate alternative data sources for thin-file customers.

• Healthcare Outcome Prediction: Patient readmission risk, disease progression modelling, and hospital resource optimisation for healthcare providers .

Data Sources We Work With

Category	Examples
Transactional	ERP systems, POS data, payment gateways
Behavioural	Web analytics, app usage logs, CRM interactions
IoT & Sensor	Machine telemetry, environmental sensors, GPS
External	Weather data, economic indicators, social media
Unstructured	Customer reviews, support tickets, emails

Our Methodology

1. Business Discovery: We work with your team to define what “accurate” means for your use case — precision, recall, RMSE, or business KPIs.
2. Data Engineering: Building robust ETL pipelines that clean, transform, and feature-engineer your data. We handle missing values, outliers, and temporal leakage with rigour.
3. Model Development: We evaluate multiple algorithms (classical ML, deep learning, ensembles) and select the best performer based on cross-validation on your holdout data.
4. Interpretability: Every model comes with SHAP/LIME explanations so stakeholders understand why predictions were made. Critical for regulated industries.
5. Deployment & Monitoring: Real-time or batch prediction APIs, automated retraining triggers, and drift monitoring dashboards.

Technology Stack

• Languages: Python (scikit-learn, XGBoost, LightGBM, CatBoost)
• Deep Learning: PyTorch, TensorFlow (for temporal and sequential data)
• Time Series: Prophet, statsmodels, Nixtla, ARIMA/SARIMA
• MLOps: MLflow, Kubeflow, Airflow for orchestration
• Visualisation: Power BI, Tableau, Streamlit dashboards
• Cloud: AWS SageMaker, Azure ML, GCP Vertex AI

Whether you are a startup or an enterprise, our predictive analytics services turn your historical data into your greatest strategic asset. Contact us to schedule a data readiness assessment.