AWS for the parts that need it.
We use AWS selectively.AI services through Bedrock, file storage on S3, and compute when serverless is not enough. Not everything belongs on the edge.
aws.amazon.com ↗We don't run everything on AWS, and that's deliberate. Most of our frontend and API work deploys on Vercel, but when a project needs object storage, AI model access, or compute that doesn't fit the serverless model, we reach for AWS. S3 handles file uploads with presigned URLs so sensitive documents never pass through our application servers. Bedrock gives us access to foundation models for AI-powered features without managing GPU infrastructure. We use AWS where it's the best tool, not as a default for everything.
AWS is the most complete cloud platform available. When a project needs services beyond what an edge platform provides (durable object storage, AI model inference, message queues, or managed databases), AWS has a production-grade answer. We pair it with Vercel rather than replacing Vercel, using each platform for what it does best. This gives our clients enterprise-grade infrastructure without enterprise-grade complexity.
AI-Powered Features
AWS Bedrock for foundation model access: text generation, summarization, and intelligent document processing.
Secure File Storage
S3 with presigned URLs for file uploads and downloads. Documents never pass through the application layer.
Backend Compute
EC2 and Lambda for workloads that need persistent connections, long-running processes, or specific runtime environments.
