Siti Nurhayati Syafaningrum@syafaningrum

Indie developers and early-stage startups can write code fast, but deployment decisions — which provider, which region, how much compute, how to control cost — are a different skillset entirely. Getting it wrong means wasted budget, over-provisioned resources, or failed deployments, and most small teams don't have a dedicated DevOps engineer to make these calls correctly. DeployBuddy Intelligence solves this by analyzing a repository's actual code — stack, dependencies, architecture patterns — and generating a tailored recommendation for provider, region, resources, and estimated cost. That recommendation is compiled into a validated DeployBuddy Blueprint (a structured JSON spec) that the DeployBuddy Deploy Agent can execute directly across providers like Vercel, Railway, Cloudflare, and AWS, complete with health checks post-deploy. The pipeline runs through 8 coordinated sub-agents — Repository Analyzer, Context Builder, Prompt Composer, an LLM core, FinOps cost estimator, IaC generator, and Blueprint persistence/validation — all orchestrated through a single LLM call per cycle for efficiency. The result is a startup-oriented product: turning deployment expertise most indie teams don't have into an automated, repeatable, auditable workflow.

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