NeenOpal Inc.

NeenOpal Intelligent Solutions is a data and AI consultancy that provides technology and professional services. The organisation operates from Canada (a Canadian presence in Fredericton is referenced) and maintains operations and partnerships across India and international markets evidenced by participation in events in Dubai, Toronto, Washington DC, Mumbai, Kolkata, and New Jersey.

Services and Capabilities

• Business intelligence and dashboard development: delivery of BI implementations using Tableau, Power BI, and Looker, including dashboard wireframing and exportable designs.
• Data engineering and cloud data platforms: design and build of scalable data pipelines, lakehouse and streaming architectures, and cloud data engineering for analytics and machine learning workloads.
• Cloud modernization and managed services: migration of legacy systems to cloud-native architectures, design of microservices and serverless platforms, and delivery of managed cloud operations on providers such as AWS.
• AI and machine learning solutions: development of AI-driven features, agentic AI for metadata enrichment, generative AI prototypes, and analytics-ready models integrated into product and operational workflows.
• SaaS product engineering: end-to-end product strategy and development for cloud-native SaaS offerings, including UI/UX design and integration of AI-enabled capabilities.
• Web and digital analytics: GA4 auditing, anomaly detection, funnel and conversion analytics, and continuous performance monitoring for websites and digital products.

Industry Focus

• Media and entertainment: development of autonomous metadata enrichment systems that extract, validate and update content metadata.
• Education technology (EdTech): implementation of streaming-first data architectures and real-time ingestion using Microsoft Fabric to support analytics and ML workloads.
• Healthcare and life sciences: analytics and BI solutions such as market simulation tools built in Power BI to model scenarios and support strategic planning.
• Retail and consumer goods: inventory optimization and analytics implementations for sales and operational reporting.
• Logistics and manufacturing: application of machine learning and real-time monitoring for supply chain and smart manufacturing use cases.