Insight Dynamics offers a cloud‑native analytics platform that aggregates ERP, IoT, and third‑party data into a centralized data lake with real‑time streaming and over 30 pre‑built connectors. The platform provides configurable KPI dashboards, AutoML‑driven demand forecasting and inventory optimization, and a what‑if simulation engine accessible via web UI and REST/GraphQL APIs, with role‑based access control and end‑to‑end encryption for enterprise security.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises with complex supply chains often rely on fragmented ERP, IoT, and third‑party systems that store data in isolated silos. The lack of real‑time visibility and unified analytics hampers accurate forecasting, leads to sub‑optimal logistics decisions, and increases operational costs.
Solution
Insight Dynamics delivers a cloud‑native analytics platform that consolidates heterogeneous data sources into a centralized data lake. The platform normalizes and streams data in near real‑time, exposing configurable KPI dashboards and drill‑down visualizations for operational monitoring. Built‑in machine‑learning pipelines generate demand forecasts, inventory optimization recommendations, and risk alerts, enabling proactive supply‑chain adjustments. Users can run scenario‑based what‑if analyses through a web UI or programmatically via RESTful APIs that integrate with existing ERP and MES systems. Role‑based access control and end‑to‑end encryption ensure data security while supporting multi‑tenant deployments for large enterprises.
Target Audience
The primary customers are supply‑chain, operations, and finance teams at mid‑size to large enterprises that run complex ERP environments and require unified, predictive analytics for logistics optimization.
Features
- Over 30 pre‑built connectors for major ERP (SAP, Oracle, Microsoft Dynamics), IoT gateways, and external data feeds, with customizable ETL pipelines
- Real‑time streaming ingestion using Apache Kafka and incremental loading into a columnar data lake (Parquet on S3/ADLS)
- Interactive KPI dashboards built on React/TypeScript with drill‑down, anomaly detection, and auto‑generated alerts
- AutoML framework that trains and serves demand‑forecasting, inventory‑replenishment, and lead‑time prediction models (TensorFlow/PyTorch)
- What‑if simulation engine allowing users to modify input variables and instantly view impact on key metrics
- RESTful and GraphQL APIs for embedding analytics into downstream applications or custom reporting tools
- Granular RBAC and SSO integration (SAML, OAuth2) with audit logging for compliance (ISO 27001, GDPR)
- Horizontal scalability via Kubernetes orchestration, supporting multi‑region deployments and auto‑scaling compute resources