Overview
What Harumi is, how a project is organized, and where to go next.
What is Harumi
Harumi is an AI-assisted platform for building, running, and scheduling operations research and optimization models. Every project is backed by a real git repository: you (or Harumi AI Chat) write Python code against a solver kernel (OR-Tools or Gurobi), commit it, run it, and see the result on the project's dashboard.
There are no notebooks or manual file uploads to configure — your code, its run configuration, and your data connections all live in the project's repository and settings, versioned like any other git project.
How a project is organized
Every project has six sections, available from the project sidebar:
| Section | What it's for |
|---|---|
| Dashboard | The default view. Shows the latest run's results, recent runs, and any scheduled runs. |
| Documentation | Markdown documents for the project — write down business rules, assumptions, or design notes. |
| Code | Browse, edit, and commit the project's git repository directly in the browser. |
| Data Sources | Connect external databases (PostgreSQL, MySQL, SQL Server, Oracle) to query from your code. |
| Chat | Harumi AI Chat — ask questions, have it read/write project files, or route a request straight to the solver. |
| Settings | Rename the project, manage Secrets (environment variables for your code), and repo details. |
A run is driven by two files committed to your repository:
harumi.toml— declares the command Harumi executes and the compute kernel (CPU/RAM and solver image) to run it on.dashboard.toml— declares the widgets (metrics, tables, charts) shown on the Dashboard, bound to the JSON your run writes tooutput/output.json.
Where to go next
Quickstart
Create a project and get your first run showing on the dashboard.
Platform tour
Documentation, Code, Data Sources, Secrets, and Harumi AI Chat, in detail.
harumi CLI
Run projects, manage data sources, and fetch results from your terminal.
API reference
Pull a project's run outputs into external systems.