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Amazon Bedrock
Foundation models and Gen AI application layer.
AI Isn’t the Future of Your Business.
It’s the Present.
The businesses that lead their industries over the next five years are the ones embedding AI into their operations today — not as a pilot project, but as a core capability layer. Cloudtry’s Gen AI Services help you move from ‘AI curious’ to ‘AI operational’ — building intelligent capabilities on your existing AWS infrastructure using the right tools, the right architecture, and a team that has already built and shipped AI systems in production.
What We Build
Agentic AI Systems
Cloudtry builds Agentic AI systems that autonomously monitor, decide, and execute across your business workflows — triaging support tickets, managing infrastructure alerts, processing documents, coordinating between systems — without waiting for a human to trigger each step. Think of it as giving your operations a team member that never sleeps, never misses a signal, and gets faster the longer it runs.
AI-Powered Operations Automation
Our proprietary AI DevOps Agent monitors your infrastructure, triages alerts, executes routine runbooks, and keeps your systems healthy without human intervention. We can deploy this as a standalone capability into your environment, dramatically reducing the ops burden on your engineering team.
LLM-Driven Product Features
We design and build LLM-powered features into your product — conversational assistants, document intelligence, recommendation engines, natural language search, and more — using Amazon Bedrock, SageMaker, and leading foundation models including Claude, GPT-4, and Llama.
Retrieval-Augmented Generation (RAG) Systems
Build AI systems that reason over your own data — internal knowledge bases, product documentation, customer records, support history — using RAG architectures deployed on AWS. Your AI assistant, trained on your context, serving your users or internal teams.
AI-Powered Business Process Automation
Identify the repetitive, time-consuming processes in your business and replace them with AI-driven workflows. Automated document processing, intelligent data extraction, AI-assisted customer support triage, and smart routing systems — designed and built on AWS.
MLOps & AI Infrastructure
For teams building their own ML models, we set up the full MLOps pipeline — training, evaluation, versioning, deployment, and monitoring — using AWS SageMaker and related services. Production-grade AI infrastructure, engineered to scale.
AWS AI Services We Work With
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Amazon SageMaker
ML training, deployment, and MLOps pipelines.
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Amazon Q & AWS AI Services
Lex, Comprehend, Textract, Rekognition, Polly, Translate.
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AWS Lambda + EventBridge
Serverless AI workflow orchestration.
Who This Is For
AI Without Infrastructure Overhead
Product teams that want to add AI-powered features without building ML infrastructure from scratch.
Automation for Operations Efficiency
Operations teams drowning in manual, repetitive tasks that AI can handle.
AWS AI Strategy for Founders
Founders who understand that AI is a competitive advantage but don’t know where to start on AWS.
From Experimentation to Production
Engineering teams that have experimented with AI in isolation and now need to productionise it properly.