Speech AI Platform Infrastructure
Infrastructure build and hardening for an enterprise AI speech-and-language platform: automatic speech recognition, streaming speech-to-text, LLM inference, and summarisation services running as containerized workloads on AWS ECS behind a Kong API gateway.
The Challenge
An enterprise client's speech and language services needed production-grade foundations: repeatable deployments across multiple environments and regions, a hardened network and security posture, and support for both open-source and enterprise distributions of the same service stack.
What We Built
We built and hardened the platform on AWS ECS with a Kong gateway in front, and a GitOps deployment flow using Terragrunt and Atlantis, so every infrastructure change ships through a reviewed pull request. The security posture covers multi-tier VPCs with NACLs and endpoints, IAM permission boundaries, TLS for EFS and S3, and ALB access logging. Model weights sync automatically to EFS, a shared GPU development environment serves model-inference workloads, and observability ships through an OpenTelemetry collector.
The Outcome
A hardened, multi-environment AI platform where every infrastructure change is reviewed, repeatable, and auditable, and where model updates reach production without manual handling.
This project was delivered by our cloud infrastructure & devops practice.
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