deplovox
infra god turns a plain-English description into a grounded, independently-verified deployment plan for your own AWS, Azure, or GCP account — cited to the cloud's own docs and checked before you ever see it. Not a walled garden. Not a chatbot guess.
1 free run per day · no signup
deplovox plans infrastructure you own and can verify — the harder, more honest problem. That's the point, not a footnote.
The plan deploys to your AWS, Azure, or GCP account. You own the infrastructure and the bill — there's no deplovox runtime to lock into, and nothing to migrate off later.
Grounded in the cloud's own docs and cited, then checked by real tools — `terraform validate` with pinned providers, checkov + tflint scanning, and a deterministic zero-dangling-reference check — before you ever see it.
One description maps to AWS, Azure, or GCP, grounded in each cloud's own idiomatic services — not a lowest-common-denominator template, and not a bet on a single vendor.
Every plan leads with a computed confidence read — architecture, IaC completeness, and deployability, plus how much manual work is left — derived from its own validation checks. Honest precisely because it isn't always 100%.
Take your app to infrastructure you own — same app, a cloud account you control. See how each maps to a real, verified deployment build.
deplovox turns a plain-English description of your app into deploy-ready infrastructure-as-code for your own AWS, Azure, or GCP account — Terraform or CloudFormation. What makes it different isn't that it can generate IaC (anything can). It's that deplovox tells you, honestly and precisely, how much to trust what it just gave you — and refuses to dress up a guess as a guarantee.
The verified builder · the golden path
For the app shapes deplovox knows — a web service and a database, a multi-service app, one with a CDN, a custom domain, or user login — it doesn't write infrastructure from scratch. It assembles it from battle-tested, independently-verified building blocks, checks the result against structural rules (database is private, secrets are referenced not hardcoded, load balancing is wired correctly), prices it against dated cloud pricing, and cites the official docs behind each decision. The result is deploy-ready, deterministic, and costs a fraction of a cent. This path covers the large majority of common app shapes.
The AI path · the honest fallback
For an unusual shape it doesn't have a verified recipe for, deplovox asks a frontier AI model to generate the infrastructure — and then does something most tools don't: it repairs and labels that output before you see it. Every AI-generated result is clearly stamped “AI-generated · unverified · review before deploy,” and its confidence score is attributed to the AI, not to a deplovox verification. You are never handed a guess disguised as a sure thing.
When the AI writes infrastructure, deplovox runs a deterministic repair pass over it first. It reads the infrastructure as a graph of resources — not as text — so the same checks work across Terraform and CloudFormation. Where it finds a fixable mistake (a CDN certificate in the wrong region, a container tag set to mutable, an invalid resource property), it fixes it automatically. Where a mistake can't be fixed safely — like narrowing an over-broad permission, or a DNS zone only you can provide — it does not guess; it flags it clearly for you to resolve.
It can never make it worse
Each fix is applied on a copy and kept only if it strictly removes the problem without introducing a new one. This is proven exhaustively, not assumed.
It never invents
deplovox fixes what it can prove and honestly flags the rest — it will not fabricate a value it doesn't have.
The point isn't a perfect answer every time. It's an honestone — verified where we can prove it, repaired where we safely can, and clearly labeled everywhere else. That's infrastructure you can act on with your eyes open.
The request
“A Next.js web app with a Node API and a background worker, a Postgres database and Redis cache, on a custom domain behind a CDN, with user login. Deploy it to my AWS account.”
Assembled from tested modules: multi-service ALB routing, per-service ECS, a CDN, a custom-domain certificate in the correct region, Cognito login, and a private database.
Deploy-ready · reconciliation passed · cited to official docs · cost floor computed.
~3.6s · ~$0.006
“Built from parts we've already verified — you can deploy this.”
The AI generated the template; deplovox's repair pass then auto-fixed the fixable faults (moved the CDN certificate to the required region, corrected an invalid resource property) and flagged the ones only you can resolve (your DNS hosted zone).
Auto-repaired · never-worse guaranteed · honestly labeled · review before deploy.
“A guess — but a repaired, clearly-labeled one. You always know what you're holding.”
Why this is more dependable
infra god grounds every plan in the target cloud's own services — not a lowest-common-denominator template. Pick a cloud, or ask it to recommend one.
S3 + CloudFront, ECS/Fargate, Lambda, and RDS — the AWS-native path for your workload, with CloudFormation or CDK.
Static Web Apps, Container Apps, Front Door, and Azure SQL, mapped to how Azure actually wants it, with Bicep or the CLI.
Cloud Run, Cloud Storage + Cloud CDN, and Cloud SQL or Firestore, with the matching gcloud commands and Terraform.
We ran the same complex multi-tenant SaaS nine times — across AWS, Azure, and GCP, at three experience levels. Every plan is grounded, cited, consistency-checked, and reproducible — and when a check finds a gap, we show it, not hide it.
Real output, cited to the cloud's own docs
RDS PostgreSQL 16, Multi-AZ instance for the 99.9% availability target [Source 1] → docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Welcome.html
A grounded deployment guide should cost less compute than the trial-and-error it replaces. Here's how deplovox keeps each run lean — and how we stay honest about what it costs.
Ask the same thing twice and the second answer is served straight from cache — no additional model compute.
The small, fast Haiku model handles retrieval, security review, and QA; the larger Sonnet model is reserved for architecture and infrastructure code. Not everything runs on the big model.
Infrastructure code is generated in bounded sections, so a fix re-runs one small section instead of regenerating the whole template from scratch.
A single grounded, cited answer replaces a long back-and-forth of chatbot trial-and-error — far fewer total tokens to reach something you can actually deploy.
Every result shows an estimatedcompute footprint — the energy and CO₂e of the model inference that produced it — alongside the exact formula and sources. It's an estimate for transparency, not a measurement and not a marketing claim. Same “use retrieval only when it earns its keep” ethos as our open-source ragornot.
Watch infra god turn three plain-English requests into verified deployment builds — and decline the one it can't guarantee — with every gate, cost line, and citation shown.
The first 100 testers get a complete deployment guide — free, and yours to download. No account, no credit card.
Limited to the first 100 testers.