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A D2C customer-retention SaaS company, building for Shopify Plus brands, needed a production-grade backend for its one-click cashback engine. The existing setup couldn't credit or redeem cashback reliably — there was no atomic guarantee on redemptions, leaving room for race conditions and double-spend, and balances weren't real-time at checkout, which forced page reloads and broke the one-click experience. It also lacked multi-tenant isolation to serve many brands at once, and ran on always-on infrastructure that carried idle cost regardless of order volume. On top of all that, retention nudges were generic promotional blasts with no personalisation or timing, producing low open rates and weak redemption conversion.

CloudTry rebuilt the engine on a fully serverless AWS architecture spanning four flows — earning, AI nudges, balance display, and redemption. At its centre, Amazon EventBridge schedules a reminder for each customer's predicted optimal moment and Amazon Bedrock (Claude Haiku) generates a personalised message for that specific shopper, at a cost of under $0.0002 per nudge — replacing generic blasts with individually tailored, well-timed reminders that lift open rates and redemption conversion. Alongside the AI layer, DynamoDB conditional writes eliminated double-spend, balance retrieval at checkout dropped to under 100ms, and a multi-tenant design now supports unlimited brand clients with full data isolation on a pay-per-transaction model with zero idle cost. An established brand client saw a 32% improvement in repeat purchase rate post-deployment, and the engagement closed at 4.75 out of 5.

A document intelligence software provider was running its extraction pipeline on rule-based OCR, which managed only 70–75% field accuracy and struggled with complex, unstructured documents. Around 35% of all documents needed manual review at 15 to 20 minutes each, creating a serious operational bottleneck, and the EC2 infrastructure behind the pipeline ran around the clock regardless of document volume, driving up idle compute costs. The provider needed a Generative AI approach that could handle unstructured and semi-structured documents accurately, cut manual intervention sharply, and slot into its existing AWS environment.

CloudTry rebuilt the pipeline on a fully serverless AWS architecture, pairing Amazon Textract for extraction with Amazon Bedrock (Claude Haiku) for classification, validation, and gap-filling. Field extraction accuracy rose from 70–75% to 92–95%, per-document processing dropped from 15–20 minutes to under 30 seconds, and the manual review rate fell from roughly 35% to under 8%. Coverage expanded beyond pre-defined templates to unstructured and semi-structured documents across all formats, while moving off always-on EC2 to a pay-per-document model lowered infrastructure cost by an estimated 35% — with results benchmarked across 500 documents and the engagement closing at 4.25 out of 5.

OneAlpha, a fintech building AI-powered financial analytics and capital markets solutions, was running on over-provisioned EC2 instances around the clock, which meant high fixed infrastructure costs and the constant operational overhead of manual patching and server management. Financial document analysis was done entirely by hand, taking two to four hours per document, and the company had no LLM capability in production. It needed a cloud-native architecture that could process financial data with low latency, bring Generative AI into production for document analysis, and hold to the security and compliance standards expected in capital markets.

CloudTry delivered a fully serverless, Bedrock-native architecture that cut document analysis from two-to-four hours to under 60 seconds and lowered infrastructure cost by an estimated 40–50% by replacing always-on EC2 with pay-per-invocation Lambda. The engagement brought OneAlpha's first production LLM capability live through Amazon Bedrock, left zero EC2 infrastructure to manage post-deployment, and strengthened the security posture with IAM least-privilege scoping, VPC isolation, and CloudWatch audit logging across the pipeline — closing at a customer satisfaction score of 4.75 out of 5.

Meet round-the-clock demand for instant, trustworthy answers to common Vedic queries, without stretching a limited pool of live pandits or risking AI invention on spiritual content.

A WhatsApp AI chatbot built on a serverless RAG architecture on AWS, with every answer drawn from Live Pandit Ji's own curated Vedic knowledge base. Response times dropped from up to several hours to under two seconds, with 24/7 availability, zero hallucinated answers, and routine queries lifted off the live astrologers' plates.

FarziEngineer was experiencing significant operational and financial challenges with their Google Cloud Platform infrastructure, limiting their ability to scale efficiently and serve enterprise clients effectively.

With the successful migration to AWS complete, FarziEngineer is now positioned to execute on this ambitious roadmap, leveraging AWS's comprehensive service portfolio to drive innovation and scale their SaaS commerce platform globally.

Hotel Ashiyana Residency's Digital Transformation: Website Optimization & Database Migration

The modernized infrastructure delivered transformative results across performance, reliability, and business growth with up to 10× improvement in booking system responsiveness, 99.99% web service availability through redundant architecture, and a 34% rise in direct website bookings within the first quarter. CloudFront edge delivery ensured a seamless experience across devices and locations, while a centralized admin panel reduced manual errors and operational delays. An optimized cost structure through autoscaling EC2, RDS, and S3 tiering combined with automated backups, monitoring, and alerting strengthened operational resilience and reduced risk, and the platform's newfound agility in launching promotions and campaign landing pages positions the business for sustained, scalable growth.