Planned

Flux

Metrics & Dashboards

Give Claude eyes into your business metrics. AI reads dashboards, spots trends, and alerts you to what matters.

Before

How Claude sees your app today

C
Claude
Y

You

How's our conversion rate trending this week compared to last?

C

Claude

I'd like to help, but I don't have access to your metrics.

I can't see conversion rates, signups, revenue, or any business data.

Could you export the data from your analytics dashboard and share it?

Y

You

*Opens Datadog, creates custom query, exports CSV, uploads to chat...*

After

How Claude sees your app with Flux

C
Claude
Flux connected
Y

You

How's our conversion rate trending this week compared to last?

C

Claude

Let me check the conversion metrics...

Using flux.query_metric

flux.query_metric("conversion_rate", compare: "week_over_week")

Response

This week: 3.2% conversion rate

Last week: 2.8% conversion rate

Change: +14.3% (statistically significant)

Great news! Conversion is up 14.3% week-over-week. Let me check what changed...

Using flux.correlate

flux.correlate("conversion_rate", with: "recent_changes")

Insight: The conversion bump correlates with the checkout redesign deployed Tuesday.

Mobile conversion specifically jumped 22%. Desktop unchanged.

Analysis time: 4 seconds

The Difference

Without Flux

  • Claude can't see your metrics
  • You export CSVs and screenshots
  • Manual correlation of data
  • Insights arrive days late

With Flux

  • + Claude queries any metric instantly
  • + Natural language questions work
  • + AI finds correlations automatically
  • + Real-time insights, not reports

How It Works

1

Collect metrics automatically

Business metrics, technical metrics, custom events—all captured.

Flux.track("signup", user: current_user, plan: "pro")

2

Build dashboards visually

Drag-and-drop dashboard builder. Or let AI create them for you.

4 widgets, 2 charts, 1 funnel

Conversion Dashboard

3

Query via MCP

AI agents can query any metric, any timeframe, any comparison.

flux.query_metric("mrr", period: "last_30_days")

4

AI spots anomalies

Baseline learning detects when metrics deviate from normal.

Churn rate 2.3x higher than baseline

The Tools AI Uses

Available via MCP (Model Context Protocol)

flux.query_metric(name)

"What's our current MRR?"

flux.compare(metric, periods)

"Compare this month to last"

flux.correlate(metric, events)

"What caused the conversion drop?"

flux.forecast(metric, days)

"Predict next month's revenue"

Get Started

One gem. Zero config. Works in 30 seconds.

# Add to your Gemfile

gem 'brainzlab'

# Run bundle

$ bundle install

# That's it. Metrics are being collected.

Coming Soon

We're building Flux as part of Phase 1. Follow along to get early access.