Make governance the default. Across every team.
For platform and internal-developer-platform teams responsible for standardizing how an entire organization builds software with AI.
Tool sprawl, inconsistent standards, no central context.
Tool sprawl and Shadow AI
Every team adopts its own AI tooling. You are accountable for the output and govern none of the inputs.
Inconsistent standards
Architectural rigor and review discipline vary team by team, project by project — there is no golden path AI is obliged to follow.
No central context
Model access, token spend, and policy enforcement happen outside any platform you control, so cost and compliance are quarterly surprises.
One governed surface. Inherited by every team.
Central bus for LLMs
One governed surface replaces fragmented tooling and removes the Shadow AI gap.
Architecture as a contract
Approved stacks, sanctioned libraries, and design patterns are enforced on every project, inherited by every team — not re-litigated per repo.
FinOps and traceability
Context is restricted to project boundaries, blocking deviation and token waste — giving you FinOps and full traceability across the org.
A platform team's job is to make the right path the easy path. With AI in the loop, that means one governed surface instead of a dozen ungoverned ones. Demand tooling that centralizes model access, encodes your architecture as a contract every team inherits, and meters consumption so cost governance is not a quarterly surprise. Shadow AI is not a user discipline problem — it is a platform gap, and it is yours to close.
The expandev founding teamCodify the golden path. Promote it.
Codify your golden-path stack as a declared Architecture template. Onboard two pilot teams onto it and use the Analyzer's compliance findings to measure real adherence. Once the path proves itself, promote the template as the organization-wide default.
See expandev applied to your stack.
Tell us about your team and we'll tailor a walkthrough to your stack, your governance needs, and the way you ship.