Build your BI dashboards
with coding agents

Use Codex, Claude Code, or any coding agent to build your models, metrics, and dashboards. Locally in your IDE, or in the browser with our Development Copilot.

secure.holistics.io/reports/revenue-dashboard

Live preview

Your dashboard will build here

claude · ~/analytics
>
Build Revenue dashboard (0m 00s · ↓ 0.0k tokens)
esc to interrupt · ctrl+t to hide tasks
Holistics local agentic development · docs.holistics.io
In the workspace · Development Copilot

Your agentic BI developer, built into Holistics

Build datasets, define metrics, and generate dashboards in plain English — no setup, right in your browser.

In your IDE · Local agentic development

Bring your own coding agent

Connect your favorite coding agents — Claude Code, Cursor, Codex — to your BI codebase. Run queries, build metrics, and preview results live through Holistics' CLI and MCP tools.

A real session — a coding agent building Holistics analytics from the terminal.

1
claude · ~/analytics
/setup-amql-development
Holistics CLI authenticated
MCP server connected
Live sync started

Clone & connect

git clone your repo, then run /setup-amql-development — one command wires up the CLI, MCP, and live sync.

2
revenue.page.aml
Add a Revenue dashboard with QTD & YTD KPIs
+ Dashboard revenue {
+ KPI qtd_revenue { … }
+ BarChart monthly_rev { … }
+ }

Build by prompting your agent

Ask Claude Code, Cursor, or Codex. It explores your workspace over MCP and writes the AML.

3
app.holistics.io/revenue
QTD$4.8M
YTD$14.2M
Margin67%

Preview live, instantly

Every save syncs to a cloud dev branch in seconds. See the real dashboard and tweak it back.

4
Add Revenue dashboard #42
+128 −4 · 3 files changed
AML validate passed
1 review approved
Merge pull request

Ship like software

Commit, open a pull request for review, and merge — or publish straight to production.

Your machine, Holistics' cloud — three wires between them

Your agent edits AML on disk; three connections do the rest. No magic, no lock-in — just code, MCP, and Git.

Local agentic development architecture — coding agent and CLI on your machine connected to the Holistics cloud runtime, dev branch, and prod branch.
MCP — read & reason

Your agent inspects schema, runs AQL, and searches the docs against your real warehouse. Grounded, never guessing.

CLI sync-code — live preview

Every save streams to a cloud dev branch; the real dashboard renders within seconds, and edits in the UI sync back to your files.

Git — ship

Clone and push your BI as code. Open a pull request, validate in CI, and merge to publish the prod branch.

Why agents can actually build your analytics

Agents need a substrate they can read, reason on, and change safely. Holistics gives them three.

Analytics-as-code

Every model, metric, and dashboard is typed AML in Git. Agents edit real code — with history, branches, and pull requests — not opaque click-config.

A semantic layer agents reason on

Agents generate AQL against your governed definitions, not raw text-to-SQL. The result is readable, verifiable, and grounded in metrics your team already trusts.

Reachable over MCP

The MCP server gives any agent live workspace access — explore models, run queries, inspect schemas — so it reasons from the same definitions everywhere.

Whatever builds it, the output is governed

Agent-authored or hand-written, every change runs through the same guardrails.

Grounded in the semantic layer

Agents compose from endorsed metrics and relationships — never inventing numbers from scratch.

Versioned and reviewed

Every change is code in Git: diffs, pull requests, and approvals before anything reaches production.

Traceable lineage

Each metric traces back to its definition and the models it's built from, so answers hold up.

What teams building on Holistics say

I'd score AQL a 9 or 10. It's up there with the best tools I've used. It's really cool that we can now define metrics based on other metrics, stacking them on top of each other.

Ian

BI Engineer, DNSFilter

avatar
Bulk edits and refactors happen in code, not by clicking through a UI for an afternoon. It keeps a lean data team fast.

Senior data engineer

Funding Societies

Non-technical users run their own analyses now. The data team stopped being the queue.

Data team lead

Optimal Workshop

Frequently asked questions

Which coding agents are supported?

Claude Code, Cursor, GitHub Copilot, and Codex all work with the local workflow via the Holistics MCP server and CLI. The in-product Development Copilot needs no setup at all.

Do I need to set anything up for the cloud Copilot?

No. The Development Copilot is built into the Holistics workspace — open a dataset or dashboard and start asking. Local agentic development requires connecting your repo and running /setup-amql-development.

Is agent-generated work governed and safe?

Yes. Whatever creates a change, it's typed AML grounded in your semantic layer, versioned in Git, and reviewable through pull requests before it reaches production.

How do changes ship to production?

Through the same path as code: commit and push, open a PR, review and merge, then publish — manually, via the Publish API, or with an auto-publish GitHub Action on merge.

See it on your data

A 30-minute walkthrough with a Holistics engineer. We'll connect a sample of your warehouse and build something with an agent, live.