A free, browser-based tool that helps national authorities query their own GIS data within an impact polygon, then generate sector-specific, library-grounded <description> text for Common Alerting Protocol warnings.
Countries implementing Early Warning Systems (EWS) under the UN EWEA initiative face a common bottleneck: converting meteorological data into actionable, sector-specific alert language — fast, consistently, and at scale.
A flood warning that doesn't mention the school, the clinic, or the road your community depends on doesn't produce action. Specificity saves lives.
Warning officers work under extreme time pressure. Without structured support, alert language is inconsistent, incomplete, or misaligned with CAP standards.
National authorities often have GIS data on infrastructure, schools and health facilities — but no fast way to connect that data to the impact footprint of an incoming hazard.
The tool runs entirely in your browser. No account, no server, no data leaving your machine unless you choose to use an AI API.
Load your own GIS data sources — local files, ArcGIS REST services, WFS endpoints, or shapefiles. Draw a polygon on the map (or paste coordinates from a met service warning), and the tool instantly queries every layer to find what's inside: schools, health facilities, roads, population centres, critical infrastructure.
Select which layers to include in the alert. Set the hazard type, severity, and authority level — or let the tool infer the appropriate level from your data. Optionally load your organisation's pre-validated early action library (.db file) to ground the output in approved language.
The tool queries your library for matching pre-validated messages, then passes them — alongside your GIS impact data — to the AI model of your choice. It produces sector-specific <headline> and <description> blocks ready to paste into your CAP editor, each tagged by source.
Load a SQLite library of pre-validated early action messages — organised by hazard, sector, severity, and authority level. The AI uses these as its foundation rather than generating from scratch, then layers in the specific names, counts, and conditions from your GIS data.
Every output block is tagged so you always know what you're working with:
The library file is a standard SQLite .db — you own it, you control it, and it never leaves your machine. Last Larch provides a seed library covering 8 hazard types across 8 sectors.
For national authorities handling sensitive infrastructure data, data sovereignty is non-negotiable. ARIA is built around that principle from the ground up.
Shapefiles, GeoJSON files, and your .db library are loaded directly into your browser's memory. They are never uploaded to any server. Close the tab and they're gone.
Connect any OpenAI-compatible model — Claude, GPT-4o, Gemini, or a self-hosted model via Ollama. Your API key is stored only in your browser's localStorage. Last Larch never sees it.
The entire tool is a single HTML file. No server, no dependencies to install, no account to create. Open it in any modern browser and it works. Share it by attaching it to an email.
⚠ Note: When you generate descriptions using an AI API, a summary of your GIS data (feature counts, attribute names, and up to 40 sample rows per layer) is sent to the AI provider you configure. No raw geometry is transmitted. Review your AI provider's data policy if this is a concern.
You don't need to be a developer to use this tool. If you can open a browser and load a file, you can produce publish-ready alert language.
Translate forecast data into structured CAP alerts with sector-specific language — without a developer in the room. Compatible with any CAP editor.
Query your own infrastructure data against any incoming hazard polygon. Generate authority-level appropriate messaging for education, health, logistics, and more.
Support country offices in building and maintaining validated early action libraries. The .db format is portable and version-controlled.
Prototype, evaluate, and iterate on impact-based forecasting workflows. All outputs are traceable — you always know whether language came from the library or was generated.
No proprietary dependencies. Every component is open source or an open standard.
ARIA-Lex is the seed library that ships with ARIA. It contains pre-structured early action messages covering 8 hazard types across 8 sectors, organised by severity and authority level. It's a starting point — designed to be extended, localised, and validated by your organisation.
ARIA-Lex.db belowARIA-Lex.dbDownload the single HTML file, open it in your browser, and start querying your data. No account, no server, no installation. Questions or custom implementations — Last Larch is available for consultancy engagements.