Turning Foot-Traffic and POS Data into Real-Time Venue Intelligence
Our client operates a network of nightlife and hospitality venues, where each location generates massive volumes of foot-traffic and point-of-sale (POS) data every day. Without a unified way to translate this data into meaningful insights, decisions around staffing, promotions, and operations were largely reactive, cross-venue performance comparisons were nearly impossible, and revenue opportunities remained hidden inside fragmented data systems. NeenOpal partnered with the client to build a scalable, multi-tenant venue intelligence platform on AWS that transforms raw POS and footfall activity into real-time, decision-ready insights at the venue, region, and network level.
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How a Global Agricultural Equipment Manufacturer Built a Trusted Web Analytics Platform with GA4, Snowflake, and Power BI
Our client is a leading manufacturer of agricultural and industrial equipment operating across international markets, with a B2B sales model distributed through an authorised dealer and reseller network. The client's website serves as a primary discovery and research channel for prospects and distributors, where meaningful conversion actions centre on product brochure and playbook downloads rather than direct online transactions. Despite access to Google Analytics 4, the client had no reliable mechanism to trust or act on its own web data, with sampled GA4 reporting, undefined conversion events, and the absence of a structured data pipeline meaning internal stakeholders were making website and content decisions without confidence in the underlying numbers. NeenOpal partnered with the client to rebuild the analytics data foundation from the ground up, engineering a modern pipeline from GA4 through BigQuery into a multi-layer Snowflake data warehouse, and delivering a suite of Power BI dashboards that provided trusted, unsampled website intelligence for the first time.
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How a Healthcare Education Organisation Replaced Manual Survey Scoring with a Fully Automated Analytics Pipeline and Real-Time Leaderboard
Our client is a healthcare and medical education organisation that runs competitive, survey-based learning programmes for clinicians, residents, and academic medical professionals across the United States. The organisation conducts multiple educational event series, structured as races with individual laps, where participants respond to clinically oriented survey questions under time pressure, and performance is ranked across both individual questions and cumulative laps with top performers recognised and rewarded at the close of each event cycle. Prior to NeenOpal's engagement, every aspect of survey data collection, aggregation, scoring, and leaderboard generation was handled manually through Excel, an approach that introduced systematic risk of error and created significant operational burden for the internal team. NeenOpal designed and delivered an end-to-end automated pipeline, migrating the client from a fragmented, manual process to a fully governed, cloud-based analytics platform powering daily leaderboard refreshes across all active events.
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Eliminating Manual Email Triage with an AI-Driven Workflow
Our client, a metadata operations team within a large media technology company, managed a high volume of inbound scheduling support emails from broadcast networks and affiliates. Each email required manual reading, classification, priority assignment, and Jira ticket creation — a time-intensive process prone to inconsistency, duplicate tickets, and SLA breaches. NeenOpal designed and deployed an end-to-end AI-driven triage system on AWS that fully automated this workflow, combining Amazon Bedrock, AWS Lambda, and deterministic business rules to deliver accurate, auditable, and zero-touch email-to-ticket processing.
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Predicting Video Revenue Through Marketing Mix Modeling and Bayesian Forecasting
Our client, a media and entertainment company, sought to establish a scalable and repeatable process to predict video revenue based on varying marketing spend inputs. With multiple upcoming releases and limited visibility into which marketing channels drove the most impact, media planning decisions were largely manual and difficult to optimize. The client partnered with NeenOpal to operationalize a Marketing Mix Modeling (MMM) framework, enabling data-driven revenue forecasting, dynamic sensitivity analysis, and interactive scenario planning through a Tableau dashboard.
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Custom CI/CD Pipeline for Multi-Tenant SaaS Delivery on Microsoft Fabric
Our client, a SaaS product company built on Microsoft Fabric, needed a reliable and scalable way to deploy analytics content across multiple customer tenants — each with different service tiers, feature sets, and upgrade preferences. After evaluating Fabric's native deployment pipelines, critical limitations made it unfit for a multi-tenant SaaS model. NeenOpal designed and implemented a fully custom CI/CD pipeline using GitHub Actions and the Fabric REST APIs, giving the team complete control over what gets deployed, to whom, and when.
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How a Leading Gold Loan Provider Eliminated Retention Guesswork with ML-Powered Churn Prediction
Our client is a leading financial institution based in Sri Lanka, providing specialised gold loan products across a retail network of more than 50 branches and serving an active customer base estimated in the hundreds of thousands. The business model is built around short-term, collateral-backed lending, where customer retention at loan maturity directly determines portfolio revenue. Despite years of accumulated transactional data across five core SQL Server tables, the organisation had no mechanism to convert that data into customer-level insight. NeenOpal partnered with the client to build and deploy a machine learning churn prediction system, alongside a customer scoring model and Tableau dashboards, enabling the organisation to shift from reactive, instinct-driven outreach to precision-targeted retention.
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From Dashboards to Conversations: AI-Powered Real Estate Analytics with Tableau Concierge
As analytics evolve, so do the ways business teams interact with data. Traditional dashboards require users to navigate filters, build calculations, and interpret visuals manually, a process that slows decision-making and creates dependency on data teams. NeenOpal explored the capabilities of Tableau Concierge, part of the Tableau Next vision, by building an interactive real estate analytics experience that allows users to simply ask questions and get instant, visual answers powered by generative AI.
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Unifying Marketing, CRM, and Revenue Analytics Using HubSpot, GA4, BigQuery, and Power BI
A group of real estate–focused service businesses partnered with NeenOpal to unify their marketing, CRM, and revenue analytics. Data was fragmented across platforms like HubSpot, GA4, and advertising tools, making it difficult to track how marketing efforts translated into leads and revenue. NeenOpal designed an integrated analytics ecosystem using HubSpot, GA4, BigQuery, Coupler.io, and Power BI to create a scalable, reliable, and decision-ready reporting layer without disrupting the existing stack.
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Cloud Migration for Secure, Scalable Dental Imaging on AWS
Our client operates a network of dental clinics relying on on-premise servers to receive DICOM imaging batches and perform 3D reconstruction. While this setup handled day-to-day operations, it introduced significant scalability constraints, inconsistent performance, and mounting operational overhead. To modernize their imaging infrastructure, our client partnered with NeenOpal to design a secure, HIPAA-compliant cloud architecture on AWS, enabling reliable DICOM cloud migration, GPU-based medical image processing, and centralized management of sensitive dental imaging data.
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