Autonomous Metadata Enrichment with Agentic AI
Our client, a prominent entertainment company, faced persistent delays and quality issues caused by incomplete metadata within critical content systems. Manual efforts to validate and enrich records created bottlenecks and limited scalability. We built an autonomous data enrichment solution using agentic AI that detects missing fields, extracts reliable information from trusted sources, and updates databases with validated, confidence-scored insights.
Unifying Educational Data with Microsoft Fabric & Power BI
We partnered with a growing Ed-Tech SaaS provider that delivers cloud-based data infrastructure and analytics for K–12 school districts. The platform enables schools to unify their student information, learning systems, and performance data, providing real-time insights to educators and administrators. However, the provider faced significant challenges in integrating data from multiple systems, ensuring data quality, and delivering consistent, scalable analytics experiences. To address this, we implemented a modern data foundation using Microsoft Fabric, Synapse Analytics, and Power BI, completely transforming how education data is managed and visualized.
Revolutionizing BI Dashboard Creation with Mokkup.ai & AWS Bedrock-Powered Gen AI
Business users and analysts often struggle with the time-intensive and manual process of creating dashboard wireframes. NeenOpal, in collaboration with AWS, introduced an AI-powered wireframe generation and review solution via Mokkup.ai, a leading BI wireframing platform. This innovation leverages AWS Bedrock, zero-shot AI prompting, and a proprietary layout engine to automatically generate, review, and optimize dashboard designs. With over 110,000 active users across 60+ countries, Mokkup is transforming dashboard prototyping into an intelligent, streamlined experience.
Transforming Ad Performance Analytics with Amazon Q
A global advertising team sought a more efficient way to access campaign performance data across platforms like Google, Meta, and TikTok. Traditional dashboards required SQL knowledge and manual analysis. With NeenOpal, they adopted Amazon Q an AI assistant that enables natural language queries, automated reporting, and contextual insights, leading to faster and more reliable decision-making.
Scalable ILI Dashboard with AWS Lambda and Tableau Integration
A leading DEI consultancy was struggling with slow, outdated reporting systems, scattered data sources, and a lack of scalability. Their legacy database caused delays in processing survey data, leading to stale insights and a heavy manual reporting burden. NeenOpal’s Implementation Division stepped in to address these challenges by developing an Inclusive Leadership Index (ILI) dashboard using Tableau and AWS.
Real-Time Data Ingestion & Transformation Using Microsoft Fabric Streaming
A leading EdTech company partnered with our data engineering team to modernize their data pipeline infrastructure. The client faced delays in data availability, limited real-time insights, and difficulties scaling analytics and machine learning workloads due to their traditional batch-oriented ETL pipelines. To overcome these challenges, they aimed to implement a streaming-first, unified data architecture using Microsoft Fabric and its Streaming capabilities to Onelake Lakehouse.
Building a Scalable Market Insights Tool with Power Apps & SharePoint
The Power App was developed for a global pharmaceutical company, to streamline the collection of monthly, brand-wise market insights from country representatives. Users can log structured comments for multiple brands across various therapeutic areas, with options for general country-level inputs. Once submitted, comments follow an approval workflow, where designated approvers for each country review, approve, or reject the inputs. Only approved and pending comments are surfaced in a centralized dashboard for business visibility.
Structured Data Entry at Scale: A Power Apps Success Story
The client, a leading healthcare-focused organization, had long depended on a large Excel workbook to manage critical operational data. Over time, this approach became unsustainable. As data volume and user activity increased, the Excel system suffered from slow performance, frequent crashes, and the inability to handle concurrent edits without data being overwritten. The lack of validation allowed inconsistent, junk entries, while the absence of an audit trail made it difficult to track changes or maintain data integrity. These limitations began to severely impact daily operations and decision-making.
Driving Strategic Growth with Power BI Evolution Index Tool
The Evolution Index (EI) Simulator Tool was built to help the client plan strategically by simulating various market growth scenarios across countries. Built in Power BI, the tool helps users to input key variables and dynamically evaluate their impact on year-end performance. This simulation-driven approach enhances forecasting accuracy and helps organizations allocate resources effectively, driving smarter business decisions and maximizing market opportunities.
Building a Customer Churn Prediction Model for a Leading Gold Loan Provider
A leading Non-Banking Financial Company (NBFC) in Sri Lanka was facing rising customer churn and lacked the tools to effectively identify and act on early signs of risk. NeenOpal partnered with the client to develop a machine learning–driven churn prediction model that accurately identified at-risk customers, enabling timely and personalized retention strategies.