Ten integrated modules covering the full analytics lifecycle — from ingestion through decision. Each module exposes REST APIs, participates in the shared model registry, and inherits the platform's identity, audit and governance layers.
A unified engine for the five analytics disciplines — predictive, prescriptive, descriptive, diagnostic and cognitive — operating on the same governed data and model catalog for consistent, explainable results across the organization.
Distributed batch and stream compute for structured, semi-structured and unstructured workloads — with integrated data lake management and warehouse connectivity, so raw and modelled data live in one addressable estate.
End-to-end MLOps: AutoML for rapid model discovery, feature engineering workbench, distributed training, validation with performance and fairness checks, one-click deployment and continuous drift monitoring.
Managed training and inference for CNN, LSTM and Transformer families — covering vision, speech, forecasting and recommendation workloads with ONNX interoperability across TensorFlow and PyTorch.
Language understanding at enterprise scale — for support triage, document intelligence, translation, entity extraction and open-domain question answering — with multilingual support including Indic languages.
A grounded generative layer built on your organisation's data. Enterprise chatbots, report and content generation, code assistance, knowledge assistants and document summarization — with citation-first RAG and policy-aware guardrails.
Sub-second event processing with live dashboards, KPI monitoring, streaming aggregations and a configurable alert engine — for operations centres, command dashboards and mission-critical monitoring.
Executive dashboards, interactive charts, geospatial (GIS) analytics, heat maps, drill-down reporting and KPI scorecards — configurable through a drag-and-drop dashboard designer.
Governed self-service BI for business users and analysts — ad-hoc reporting, executive summaries, OLAP cubes and a dashboard designer, all fed by the same governed semantic layer.
Explainable decisioning for high-stakes environments — risk analysis, fraud detection, root-cause discovery, what-if simulation and mathematical optimization — with model-level XAI traces on every recommendation.
The default executive dashboard aggregates real-time KPIs, forecasts and anomaly alerts across configured modules. All widgets are drag-configurable and inherit RBAC from the platform's identity layer.