Coder & AWS: Why self-hosted AI workspaces are a secret weapon for regulated industries
Coder is known for its AI development infrastructure and its ability to help developers run AI-driven development workflows in consistent, governed environments with self-hosted, agent-ready workspaces that unify developer productivity and platform governance.
The company is now working more closely with AWS.
The new deeper collaboration is hoped to give software engineering working in regulated industries the ability to scale AI across the software development lifecycle with governance, speed, and cost control.
Known as a strategic collaboration agreement (SCA) to the people who wear suits, under the agreement Coder, will work with AWS to deliver self-hosted, cloud-native development environments that run inside customers’ own AWS accounts.
Coder says it gives technology leaders “a way to scale AI” across software development “without trading away control” and so, instead of fragmented local setups, teams build in standardised workspaces that run inside the company’s own AWS accounts, so sensitive code and data never leave cloud environments the organisation already owns and governs.
Developers and AI agents work in the same governed environment, with access, guardrails and auditability enforced by default through Amazon Bedrock.
Coder CEO Whiteley: Enterprises tell us the biggest barrier to scaling AI isn’t ambition — it’s the underlying development environment.
Regulated industries
For enterprises in highly regulated industries, the result is the ability to move AI initiatives out of pilot mode and into production. Organisations can recreate on-premises development environments in AWS to accelerate cloud migration, modernise legacy systems incrementally rather than through risky rewrites, and run AI workloads on cloud environments they already pay for.
Key highlights of the collaboration include (as already mentioned) self-hosted, cloud-native development environments running inside customers’ own AWS accounts; unified governance for both human developers and AI coding agents; accelerated cloud migration by recreating on-premises development environments in AWS.
There are also built-in security, access controls and auditability through Amazon Bedrock.
“Enterprises tell us the biggest barrier to scaling AI isn’t ambition — it’s the underlying development environment. As software creation expands beyond traditional engineering teams to include citizen developers and non-traditional developers, governance becomes even more critical. We give transformation leaders the leverage to scale agentic AI development with control, speed, cost efficiency, and flexibility, all inside AWS,” said Rob Whiteley, CEO of Coder.
CTOs have said that Coder on AWS has improved developer team productivity, primarily because each team member can run multiple environments and work on concurrent features with AI.
AWS: Security, access & auditability
“AI has moved from assisting individual developers to participating across the entire software development lifecycle. Coder’s collaboration with AWS gives customers a single environment where developers and AI agents operate with the security, access controls, and auditability they trust from AWS,” said Mark Relph, director of data and AI partners, AWS.
This pair say that collaboration underscores the value of Coder on AWS i.e the ability to scale AI across the software development lifecycle, turning it into a governed, auditable, and cost-efficient capability that multiplies developer productivity without increasing risk.