Engineering and SRE teams end up running a platform through a drawer full of old custom-built tools — a script here, a half-maintained dashboard there, an internal admin nobody wants to touch. Every one of them is one more thing to keep alive.
Vantage UI is a third option. Point an AI agent at your systems; it writes the control tool — declarative YAML plus Rhai logic — over a local MCP server. You get one console that fetches live state from anywhere in the organisation — databases, AWS, your own APIs, CI, CLI tools — as up-to-date records, logs and, when you want them, charts.
Unlike a tool like DataDog, which pulls all your data into its own cloud to show it back to you, Vantage leaves the data where it already lives and reads it in real time. Nothing to ingest, nothing to ship out — and you can finally retire those old custom-built things.
Build once, share with the whole team🔗
One person builds the tool. Everyone else just opens a link. Because a Vantage app is only config, sharing it is sharing a git repo — the console travels, the data never does.
One console, every backend🔗
Internal work is scattered across tools: the AWS console in one tab, your own API in another, GitHub, a terminal for that one script, the database client. Vantage pulls them into a single sidebar — each becomes a group of tables, forms and actions.
bolt Instead of juggling five tools and copy-pasting IDs between tabs, you get one console built for exactly your job — and because it's just config, it evolves as fast as you can describe the next thing.
Why teams pick it🔗
- Fast and reactive. A smart local cache (Diorama) keeps big grids instant, tables refresh in the background, and logs stream in real time — no spinners, no manual reloads.
- Far less friction than the AWS console. One purpose-built screen instead of clicking through a clunky web console hunting for the resource you need.
- Customise everything. Make any cell clickable, define your own actions and workflows, and wire up exactly the buttons your team needs — not a fixed set someone else chose.
- Peace of mind, locally. It all runs on your own machine. You can read every line of YAML and Rhai, see exactly what the tool does, and keep evolving it as the work changes.
See it in action🔗
The AWS control console example shows this shape — wrapping the aws CLI to surface exactly the resources you operate, nothing more. (Landing in the examples repo soon.)