An Omani F&B distribution-prediction ML SaaS startup
AWS-validated reference — full details available to AWS Partner Validation or on request. (Customer name held on file with VeUP.)
For the customer, an Omani F&B distribution-prediction ML SaaS startup, VeUP authored a full real-time computer-vision design plus a costed AWS POC — Kinesis Video Streams to Lambda to Rekognition Custom Labels to DynamoDB, with SageMaker quality models and a Glue/Redshift/QuickSight tier. Scoped design.
The challenge
the customer, an Omani machine-learning SaaS startup, helps F&B companies predict product distribution at the customer level by connecting and processing their data sources. It needed an AWS reference architecture for automated inventory management, quality assessment, predictive analytics, and automated reordering via computer vision — plus a costed POC entry point — to scale from a small enterprise base.
The solution
VeUP authored a full computer-vision solution design and a costed AWS Pricing Calculator POC. The designed pipeline ingests camera feeds through Amazon Kinesis Video Streams to AWS Lambda to Amazon Rekognition Custom Labels (SKU/brand recognition) to Amazon DynamoDB inventory state; Amazon SageMaker runs damage/quality models; AWS Glue unifies product databases (GS1, Open Food Facts, USDA, distributor catalogs) into Amazon Redshift with Amazon QuickSight dashboards and Amazon Forecast demand modeling; AWS Step Functions orchestrate automated reordering; and an Amazon Bedrock layer provides conversational analytics over the data so users ask questions instead of reading charts.
Production outcomes
| KPI | Result |
|---|---|
| Production outcomes | A phased AWS reference architecture (four phases over ~10-12 months, 2-client POC entry) and a costed AWS Pricing Calculator estimate (~$25,066/month for a 2-client POC across Kinesis Video Streams, Rekognition Image, S3, Lambda, DynamoDB) were delivered. Design targets stated (detection accuracy >95%, processing <2s, uptime 99.9%) are design goals, not measured production results — the pipeline is a scoped design, not a launched workload. |
| Engagement window | 2025-02-20 (costed POC); CV Services opportunity at Onboarding → 2025-05-19 (design/POC delivered); Resell + Quicksight & AI opportunities Closed-Lost |
| Cost / TCO posture | A costed AWS Pricing Calculator POC (EU/Frankfurt) projected ~$25,066/month (~$300,792/12mo) for a 2-client POC: Kinesis Video Streams (8 devices), Rekognition Image (500K images/month), S3, Lambda, and DynamoDB on-demand. This is a pre-build pricing estimate, not realized spend. |
| Lessons & continuation | Kinesis Video Streams is the natural ingest entry point for a real-time CV inventory pipeline; Rekognition Custom Labels handles SKU/brand recognition without bespoke model training; a Bedrock conversational layer over the analytics tier is what turns dashboards into self-serve answers. |
Architecture
A Well-Architected-annotated view of the previous state and the target-state AWS computer-vision design — Kinesis Video Streams ingestion through Rekognition, SageMaker, and the analytics tier — mapped to the six AWS Well-Architected pillars. Design / costed-POC reference, not a production deployment.
Amazon Kinesis Video Streams · AWS Lambda · Amazon Rekognition Custom Labels · Amazon DynamoDB · Amazon SageMaker · AWS Glue · Amazon Redshift · Amazon QuickSight · Amazon Forecast · AWS Step Functions · Amazon Bedrock