Deploy AI That Scales — On AWS
From Bedrock chatbots to full agentic AI platforms — we build, deploy, and manage intelligent systems on AWS that grow with your business.
Certified AWS Technology Partner
The AWS Services Powering Your AI
We pick the right AWS services for your use case — no over-engineering, no unnecessary costs.
Foundation Models
Generative AI
Enterprise Security
Zero ML Overhead
What You Can Build with AI on AWS
AI Customer Support
Intelligent chatbots that resolve 60%+ tickets autonomously using your knowledge base
Find out morePredictive Analytics
Forecast demand, detect anomalies, and optimize inventory with custom SageMaker models
Find out moreContent Generation
Product descriptions, marketing copy, and personalized emails at scale via Bedrock
Find out moreDocument Intelligence
Auto-extract data from invoices, contracts, and forms using AI-powered processing
Find out moreAgentic Workflows
AI systems that plan, decide, and execute multi-step business processes autonomously
Find out moreFraud Detection
Real-time anomaly detection and fraud prevention powered by ML models on AWS
Find out moreAI on AWS + Our Other Pillars
Combine AWS AI with our other expertise for end-to-end solutions
See AI on AWS in Action
Read how businesses deployed AI on AWS with Braincuber — from chatbots to full agentic platforms.
Ready to Deploy AI on AWS?
From a Bedrock chatbot in 2 weeks to a full agentic AI platform — we'll get you there.
Tell Us About Your AI Project
We'll recommend the right AWS AI stack for your use case
Most AI Projects on AWS Fail Due to Wrong Architecture and No Expertise
Without deep AWS AI expertise, you waste budget on over-engineered solutions that never reach production.
Wrong Service Selection
Most teams pick SageMaker when Bedrock is cheaper and faster. Or Lambda when Step Functions is required. Mistakes cost months.
AWS Cost Sprawl
Unoptimized AI workloads on AWS can cost 3-5x more than necessary. SageMaker endpoints left running burn $10,000+/month with zero traffic.
AI POC → Production Gap
85% of AI POCs never reach production. Lack of MLOps, monitoring, and integration expertise is the #1 reason.
Gartner: companies with expert AI partners are 3x more likely to achieve production deployment and positive ROI within 12 months.
AI on AWS Live in 2-16 Weeks
From POC to production — our proven delivery framework for any scale.
Architecture Design
Pick the right AWS services. Design data flow. Define success metrics and cost budget.
Development
Build on Bedrock, SageMaker, or Lambda. CI/CD pipeline configured. Security reviewed.
Integration
Connect AI to your CRM, ERP (Odoo), or e-commerce (Shopify). API endpoints deployed.
Production & Optimize
Deploy with monitoring. Optimize costs. Agentic workflows enabled. Ongoing support.
We tried building our AI customer support on AWS in-house for 6 months. Spent $180K. Nothing in production. Braincuber came in, rebuilt the architecture on Bedrock + Lambda in 6 weeks, and deployed. Now handling 60% of tickets automatically at $2/ticket vs $12 before.
Frequently Asked Questions
We leverage Amazon Bedrock for foundation models, SageMaker for custom ML training, Lambda for serverless inference, Step Functions for orchestration, and API Gateway for deployment. The right mix depends on your use case.