Analytics & AI Transformation: Real-World Success Stories
Discover how NeenOpal empowers businesses with AI & Data-driven transformation.
3 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.
Read case study
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.
Read case study
Transforming Retail Operations with Forecasting & BI on AWS QuickSight
Anish GangwalA leading Sri Lanka-based retail chain was looking to take its first step towards Business Intelligence (BI) and data-driven decision-making. Operating across multiple locations, they faced inefficiencies in inventory planning, vehicle utilization, and order fulfillment. With no centralized data repository or analytics framework, they lacked visibility into operational bottlenecks and customer demand trends. To optimize their retail operations, they partnered with NeenOpal to implement a data warehousing solution integrated with predictive forecasting and an interactive BI dashboard using Amazon QuickSight.
Read case study