Analytics & AI Transformation: Real-World Success Stories
Discover how NeenOpal empowers businesses with AI & Data-driven transformation.
36 case studies
Building a Multi-Capability Retail Customer Support Assistant on Amazon Connect
Nikunj MistryOur client, a large retail group selling consumer goods, approached NeenOpal for a customer support assistant for its website, along the lines of the conversational shopping assistants the major online marketplaces now offer. The brief arrived as an exhaustive list of capabilities the assistant had to cover, spanning product research, cart building, order tracking, warranty and complaint handling, post-purchase care, and escalation to a human agent. NeenOpal built the assistant as a working proof of concept on Amazon Connect, the first time the team had taken Connect into a customer engagement. A conversational layer handles the dialogue, a governed tool layer gives the assistant controlled access to customer and product information, verified sign-in gates anything account specific, and a handover path passes the full conversation to a live agent when a person is needed. The build went from brief to working demonstration in four weeks.
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AI-Augmented ETL for Automating Multi-Portal Retail Reporting on AWS
Madhumita Giribabu
A consumer beauty and personal care brand needed to bring its Walmart and Amazon supplier and performance data into a single AWS RDS PostgreSQL database. Walmart's data was split across a standard supplier API and three separate reporting portals (Retail Link, Scintilla, and Supplier One), each with its own authentication, file formats, and update cadence. NeenOpal designed a hybrid ETL platform with two ingestion paths running in parallel: an orchestrated API pipeline for the data Walmart exposes directly, and an AI-driven report retrieval pipeline for the data that fell outside the scope of the client's existing API access. Both paths converge on a shared Glue transformation layer, a common S3 staging area, and a single PostgreSQL database, with a separate one-time Spark job bringing in Amazon Vendor Central's historical data. The result is a single, config-driven system rather than a set of one-off integrations.
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Automating Signed Credit Application PDFs with HubSpot Webhooks and AWS Serverless
Mukesh GuptaOur client, a managed technology services provider, partnered with NeenOpal to automate the business credit application its customers complete when applying for credit terms. Until then the whole process ran over email. The team sent the customer a Word form as an attachment, the customer filled in their details and emailed it back, and someone then filed the completed form against the right account in Salesforce. Every application involved a round of back and forth correspondence, manual handling at both ends, and a record that existed only as a document attached to an account. NeenOpal designed and delivered HubSpot form to PDF automation on AWS, a serverless document automation pipeline that replaced the email exchange with a single link on the client's website. A customer opens the form, enters their details, and signs, and a branded PDF is generated automatically, emailed to the address captured on the form and to the client's own team, and archived in encrypted Amazon S3, while the submission itself is recorded field by field in HubSpot. Nobody sends a form out, chases it back, or files it by hand.
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Unifying Eight Disconnected Business Systems into Centralized Power BI Dashboards
Abhinav SinhaOur client, a managed technology services provider (MSP), partnered with NeenOpal to replace a fragmented, siloed reporting process with a centralized Power BI dashboard environment. Business-critical data was scattered across multiple disconnected systems, from the CRM and PSA to the service desk, client surveys data, and network monitoring tools, leaving leadership without a single view of sales, customers, operations, or the workforce. NeenOpal designed and delivered a centralized Power BI reporting solution that unifies data from all of these sources into an automated, daily-refreshed analytics layer on AWS. By ingesting each source, staging it in a PostgreSQL warehouse, and modeling it into governed Power BI dashboards across every business function, the team turned manual, spreadsheet-bound reporting into interactive, self-service insight the client can filter and act on in seconds.
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Turning Foot-Traffic and POS Data into Real-Time Venue Intelligence
Ruchir HarbhajankaOur 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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Eliminating Manual Email Triage with an AI-Driven Workflow
Alokesh PyneOur 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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Cloud Migration for Secure, Scalable Dental Imaging on AWS
Himanshu BahmaniOur 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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AI-Powered Video Persuasiveness Prediction Using Generative AI
Dhruv Chowdary
A leading non-profit organization invests heavily in video campaigns ($50K–$200K per video) to inspire audiences and drive meaningful action. However, their manual impact testing process was slow, costly, and limited to only a small subset of high-budget productions. Without a scalable evaluation method, most videos went untested, creating a high-risk content strategy with minimal feedback to guide creative decisions. NeenOpal developed a GenAI-powered video analysis solution that automatically extracts persuasive features from video content and predicts impact scores, enabling data-driven content strategy across their entire video portfolio.
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Unlocking Instant Cash Flow for Businesses Using AR Factoring Platform
The client partnered with NeenOpal to build a modern AR Factoring platform tailored for gas station businesses in the fuel and energy retail sector. The objective was to enable faster access to working capital by advancing funds against card-based receivables, while maintaining strong risk controls, compliance, and operational scalability. NeenOpal brought this vision to life by designing a fully automated, cloud-native solution that seamlessly manages onboarding, funding, repayment, and auditability.
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Modernizing Finance Data Integration & Analytics Using AWS, Snowflake, and Power BI
Monish MohantyA global manufacturing organization with regional headquarters in the United States operates across various sectors, including agriculture, construction, marine, and industrial. The company produces advanced diesel engines, diesel-powered equipment, and gas engine-based energy systems, with finance operations supporting complex, high-volume ERP-driven reporting needs.
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