AWS Cloud & AI Strategy
A workload-first roadmap for architecture, migration, data, generative AI, identity, security, cost, and operating ownership. We connect technical choices to the business result and the team responsible after launch.
Build on AWS, without losing sight of the work.
Galang AI is an active member of the AWS Partner Network, enrolled in the Services Path at the Registered tier. We help organizations design, migrate, build, secure, and operate AWS environments around measurable workloads, from practical generative AI systems to serverless applications, governed data platforms, and resilient cloud operations.
What this looks like in production
Governed AWS landing zone
One production workload, surrounded by the controls required to keep it secure, observable, and operable.
Workload objective
start with the operating outcome
Landing zone
accounts, identity, network, guardrails
Data + AI
trusted context, Bedrock, analytics
Secure runtime
serverless, containers, or hybrid
Operate + optimize
observe, govern, improve cost and quality
APN
active AWS Partner Network member
Services
Partner Path for consulting and managed delivery
Registered
current AWS Services Path tier
What we build
AWS services, delivered by operators
Amazon Bedrock & Generative AI Systems
Custom assistants, agents, retrieval workflows, evaluations, and application features built with Amazon Bedrock and the surrounding AWS services, grounded in approved knowledge and connected to real business tools.
Serverless & Application Modernization
Modernize APIs, applications, and event-driven workflows with Lambda, containers, managed services, and cloud-native patterns chosen for the workload instead of for architectural novelty.
Migration & Landing Zones
Plan and execute migrations with clear account structure, networking, identity, logging, backup, resilience, and rollback paths. The landing zone becomes an operating foundation, not another unfinished cloud project.
Secure Data & Enterprise Integration
Connect AWS to internal systems, SaaS platforms, data stores, documents, and operational tools with least-privilege access, encryption, auditable handoffs, human approvals, and explicit failure handling.
Managed AWS Operations
Ongoing observability, incident response, security and cost review, model and application updates, documentation, and workflow improvement so the environment keeps getting better after production launch.
How an engagement runs
01
Map the workload and boundary
We define the users, systems, data, risks, current AWS footprint, operational constraints, and measurable outcome before selecting services or migration patterns.
02
Build the production path
We establish the right landing-zone controls, prototype with representative data, evaluate the architecture against the real task, and connect the system to identity, telemetry, tools, and approvals.
03
Launch and operate
Production includes documentation, training, monitoring, evaluation, cost visibility, incident ownership, and a backlog for continuous improvement. We can stay engaged as the workload grows.
Common questions
AWS, answered straight
Is Galang AI an AWS Partner?
Yes. Galang AI is an active member of the AWS Partner Network and is enrolled in the Services Path at the Registered tier. The Services Path is for organizations delivering consulting, professional, managed, and value-added resale services.
What does the Registered tier mean?
Registered is Galang AI’s current AWS Services Path tier and the starting point of the partner journey. It is not the Select, Advanced, or Premier tier, and Galang AI does not claim an AWS Competency, MSP designation, Service Delivery validation, or other specialization unless AWS separately awards it.
What can Galang AI build on AWS?
Generative AI applications and agents with Amazon Bedrock, governed retrieval and knowledge workflows, serverless APIs and applications, data pipelines and analytics foundations, secure integrations, migration landing zones, and the operational controls needed to run those systems in production.
Does Galang AI only recommend AWS?
No. We recommend by workload, existing environment, security boundary, model quality, cost, latency, and team capability. AWS is often a strong fit when cloud-native infrastructure, Amazon Bedrock, broad managed services, or an existing AWS footprint are central to the work.
Put AWS to work, without the trial and error
Cloud architecture that survives production. Book a free intro call and we'll map where AWS fits in your operation, and where it doesn't.
Also a partner of
The right platform depends on the workload.
Compare the rest of our automation bench before you commit to a stack.
