Question 1

What cloud infrastructure do you need for AI workloads?

Accepted Answer

AI workloads require GPU-enabled compute, low-latency data pipelines, scalable storage, and robust MLOps tooling. Aurion Tech designs cloud architectures on AWS, Azure, or GCP that are purpose-built for training, inference, and serving AI models at enterprise scale — with security and compliance built in from day one.

Question 2

How do you migrate to cloud without downtime?

Accepted Answer

Aurion Tech uses a phased migration approach: we run legacy and cloud systems in parallel, gradually shift traffic, and cut over only when the new system has been validated under production load. This eliminates the big-bang risk and ensures zero service interruption for your users.

Question 3

What is a data lakehouse and why does AI need it?

Accepted Answer

A data lakehouse combines the low-cost storage of a data lake with the query performance and governance of a data warehouse. For AI, this means your models can access all your structured and unstructured data from a single source of truth — eliminating the data silo problem that causes most AI projects to stall.

Question 4

How do you handle data compliance and governance?

Accepted Answer

Aurion Tech builds data lineage, access controls, and audit trails into every data platform we deliver. For regulated industries like healthcare (HIPAA) and financial services (SOC 2, GDPR), we design compliance into the architecture from the start — not as a retrofit.

Cloud & Data Strategy

What this engagement delivers.

Cloud Architecture

Data Platform

Migration & Modernization

Governance & Compliance

Ready to accelerate your intelligence?