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Home/Customer Stories/Software Engineering Customer Story · Cloud & DevOps Travel, automated: DevOps + AWS for an AI booking bot How Adroitent gave a travel-tech innovator a fully automated DevOps and AWS foundation — turning an LLM-powered email booking bot from manual deployments into a scalable, one-click cloud platform. Adroitent Case FileTravel TechAWS · DevOps · CI/CD3 min read Scroll to read AUTOMATED CI/CD ✦ INFRASTRUCTURE AS CODE ✦ AWS CDK ✦ ONE-CLICK DEPLOYS ✦ SERVERLESS + GPU ✦ SCALABLE ✦ AUTOMATED CI/CD ✦ INFRASTRUCTURE AS CODE ✦ AWS CDK ✦ ONE-CLICK DEPLOYS ✦ SERVERLESS + GPU ✦ SCALABLE ✦ 01The inflection point Success outgrew manual infrastructure The customer built a sophisticated LLM-powered email booking bot — email a request like “Fly from Hyderabad to New York next Monday” and it books flights, hotels and ground transport. Moving from development to production exposed hard infrastructure limits. 01Infrastructure management: managing complex backend APIs and LLM models on AWS manually was unsustainable 02Deployment bottlenecks: no formalized CI/CD pipeline slowed the release of new AI features 03Environment consistency: code behaved differently across development, testing and production 04Architectural diversity: inefficient management of a hybrid estate spanning AWS Lambda, ECS and EC2 “ Automate the entire lifecycle — for high availability and rapid scale. From manual deploys → to one-click cloud. From manual deploys → to one-click cloud. From manual deploys → to one-click cloud. From manual deploys → to one-click cloud. 02The intervention End-to-end DevOps & cloud modernization Adroitent architected and implemented a mission-critical DevOps and AWS infrastructure, automating the AI application’s lifecycle for high availability and rapid scalability. (hover a card) 1 Automated CI/CD pipelines Fully automated Bitbucket Pipeline, triggered on merge to the target branch Smooth, consistent deployments across Development, Testing and Production Hover to expand 2 Infrastructure as Code AWS CDK + CloudFormation codified the entire infrastructure for one-click deployment Every resource — S3 to networking — version-controlled for consistency and traceability Hover to expand 3 Optimized hybrid compute ECS & EC2 for heavy LLM processing; Lambda for event-driven booking tasks Step Functions orchestrate Flight → Hotel → Cab; SageMaker trains and manages the models Hover to expand The game changer Serverless-to-GPU hybrid compute on AWS AWS ECS & EC2 for heavy-duty LLM processing and persistent backend services AWS Lambda for serverless, event-driven tasks within the booking flow AWS Step Functions to orchestrate multi-step booking logic (Flight → Hotel → Cab) AWS SageMaker to train and manage the backend LLM models AWS architecturelive ECSEC2LambdaStep FunctionsSageMakerS3CloudWatch 03The payoff Ship in minutes, scale on demand Faster time-to-market Enhanced operational efficiency Stronger governance & compliance Scalability & agility In detail — tap to open Faster time-to-marketDeployment cycles dropped from hours or days to minutes, enabling quicker feature releases and faster response to business needs. Improved deployment reliabilityAutomated, consistent deployments minimized manual errors, resulting in more stable releases and fewer production issues. Enhanced operational efficiencyAutomation reduced manual effort, freeing teams to focus on innovation and core development. Cost optimizationLower operational overhead and reduced rework optimized infrastructure and support costs. Stronger governance & complianceVersion-controlled infrastructure ensured full traceability, auditability and adherence to compliance standards. Scalability & agilityOn-demand environment provisioning enabled rapid scaling and greater flexibility for evolving demands. Improved developer experienceSimplified, one-click deployments boosted developer productivity and accelerated onboarding. The stack behind it Tools & technology AWS EC2 AWS ECS AWS Lambda AWS S3 CloudWatch SageMaker Step Functions AWS CDK CloudFormation Bitbucket Pipelines LLM Models Python / Node.js APIs FAQ Frequently asked questions What is Infrastructure as Code (IaC)?Infrastructure as Code manages and provisions computing resources through machine-readable definition files instead of manual setup. Tools like AWS CDK, CloudFormation and Terraform let teams version, review and reproduce entire environments consistently, cutting errors and enabling one-click, repeatable deployments. How does a CI/CD pipeline speed up software delivery?A CI/CD pipeline automatically builds, tests and deploys code whenever changes are merged. By removing manual steps it shortens release cycles from days to minutes, catches problems earlier, and delivers more frequent, more reliable releases with less risk. When should you use serverless (AWS Lambda) versus containers (ECS/EC2)?Serverless functions like AWS Lambda suit short, event-driven tasks with variable load and no servers to manage. Containers on ECS or EC2 fit long-running, resource-intensive or stateful workloads — such as heavy AI/LLM processing — where you need more control over compute and memory. How do you deploy and scale an LLM application on AWS?A common pattern uses SageMaker to train and host models, containers (ECS/EC2 or GPU instances) for inference-heavy work, Lambda for lightweight tasks, and Step Functions to orchestrate multi-step logic — all provisioned via Infrastructure as Code so the stack scales on demand. What are the main benefits of DevOps automation?DevOps automation delivers faster time-to-market, more reliable and repeatable deployments, lower operational cost, stronger governance through version-controlled infrastructure, and easier scalability — while freeing engineers to build features instead of managing environments. Make your platform deploy-in-minutes. Automate your cloud lifecycle — from code to production, at scale. Talk to our experts Keep reading Related customer stories Software engineering Driving digital excellence for a North American automotive leader Read story Software engineering Modernization of healthcare applications in the US Read story Software engineering End-to-end support for a North American AutoTech leader Read story View all customer stories  ·  Explore Software Engineering services  ·  Read the blog