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There's a moment every serious investor hits where a spreadsheet just stops cutting it.

For me it was about two years ago. I had money scattered across three brokerage accounts, two real estate deals, a handful of private investments, and a business with its own cash flow dynamics. Every Sunday I'd spend two hours manually updating a Google Sheet that was always slightly wrong, never complete, and never actually told me what I needed to know to make good decisions.

I needed a dashboard. Not a pretty widget that refreshed my portfolio balance. A real dashboard. One that showed me where my money was, how it was moving, what it was doing relative to my goals, and what I should probably be paying attention to that I wasn't.

It took a few months of experimentation, plenty of dead ends, and more time in Make.com than I care to admit. But I built it. And today I'm going to walk you through exactly how it works, what it cost to build, and how you can replicate the most important parts of it without needing an engineering background.

What a Real Financial Dashboard Actually Does

Let's get clear on what we're building before we get into the how.

A financial dashboard is not just an account aggregator. Mint did that and millions of people used it and learned essentially nothing actionable about their money. An aggregator shows you balances. A dashboard shows you patterns, performance, and decisions.

Specifically, a good financial dashboard does six things.

First, it consolidates. Every account, every investment, every debt, every cash position , all in one view. Not five different apps you're toggling between. One place where you can see the whole picture in under two minutes.

Second, it tracks performance at multiple layers. Not just "my portfolio is up 8.3% this year." That's the headline, but headlines don't drive decisions. Which positions are actually driving that return? Which ones are dragging? What's the correlation between your holdings and the broader market? What's your actual Sharpe ratio? These are the questions a dashboard answers.

Third, it monitors cash flow at every level , not just personal income and expenses, but cash flow at the business level and the investment level too. These interact in ways most people don't track, and the blind spots lead to genuinely bad decisions. Like pulling money from a cash-flowing investment to fund a business expense that could have been covered by receivables arriving three days later.

Fourth, it triggers alerts. If a position drops more than a threshold you've defined, you want to know immediately. If your cash reserves fall below a floor you've set, you want to know. Not when you happen to check. The moment it happens.

Fifth, it connects to your planning model. Your dashboard should be tied to specific financial goals with specific milestones and specific timelines. Not vague targets. Actual numbers. So when you look at today's snapshot, you know exactly whether you're ahead of or behind the trajectory you need to hit your goals.

Sixth, and this is where AI earns its place, it surfaces insights you wouldn't have found manually. Pattern recognition. Correlation analysis. Anomaly detection. The kind of analysis that would take hours to do in a spreadsheet , a good system does it in seconds and delivers the output in plain language.

The Stack

Here's what I'm running, layer by layer.

The Aggregation Layer

Make.com is the orchestration backbone. Most major brokerages have APIs that let you pull positions, balances, and transaction data programmatically. Make.com schedules these data pulls every morning at 6 AM, normalizes the format across different sources, and routes everything to a central Airtable database. No manual export. No copying and pasting. It just runs.

For real estate, I pull data from my property management software , rent collected, vacancies, maintenance costs, net operating income , and route it through the same Make.com workflow. Real estate is the part of most investors' portfolios that gets tracked least rigorously, which is genuinely ironic given that it's often where the most capital is deployed. Fix that.

The Data Storage Layer

Airtable is my data storage layer. It's not a traditional database, but for this use case it's close to perfect. Flexible schema, solid API, and it connects cleanly to every visualization tool I've tried. I maintain separate tables for positions, transactions, cash flow, benchmarks, and goals. Relationships between the tables let me slice data any way I need without building custom queries.

The Intelligence Layer

This is where the AI piece comes in. I run a weekly analysis using Galaxy.ai, which lets me work across multiple AI models without switching between browser tabs or managing separate subscriptions. I feed it a structured summary of the previous week's portfolio data and prompt it to identify the three most significant changes, flag any correlations worth examining, and assess whether my asset allocation has drifted enough to warrant rebalancing action.

The output takes about two minutes to review. In the past six months, this analysis has surfaced three situations I would have missed in a manual review , once a position that had quietly drifted to 18% of my portfolio without triggering any of my mental alarms, and twice an income correlation between a REIT position and interest rate moves that I needed to account for in my cash flow projections.

The Visualization Layer

The front end is Notion. I have a Notion dashboard that pulls from Airtable via Make.com and displays my key metrics in a format I can read in under five minutes. Net worth trend (trailing 12 months). Portfolio allocation versus target. Monthly cash flow by category. Income streams broken down by source. And a rolling 90-day view of business revenue versus personal expenses. Everything above a threshold I've flagged is highlighted in gold. Everything below is highlighted in red. Most weeks it's green and I move on.

Building Yours: The 72-Hour Version

I'm not going to pretend you can build exactly what I described over a weekend. But you can build a functional, genuinely useful version in 72 focused hours if you sequence it correctly. Here's the accelerated path.

Hours 1 to 3: Define Your Metrics

Before you touch any tool, write down the ten numbers you most need to see every week. For most people this means total net worth, liquid assets, portfolio return versus benchmark, monthly cash flow (in and out), debt balances and associated interest costs, real estate equity, business revenue, personal savings rate, emergency fund runway (months of expenses covered), and one goal-specific metric tied to your biggest near-term financial objective.

Write these down. They become your dashboard requirements. Every tool and every connection you build serves one of these numbers. Without this list, you'll build something that looks impressive and tells you almost nothing useful.

Hours 3 to 8: Set Up Airtable

Create a base with tables for accounts, positions, and monthly cash flow. Manually enter your current data now , don't wait for automation. Get the data in so you have something real to look at immediately. You'll automate the data collection in the next phase. Manual entry for the first pass takes about two hours and forces you to think carefully about how you want to categorize things.

Hours 8 to 16: Connect Make.com

Start with your most important data source , probably your primary brokerage account. Use their API or a webhook connection to start pulling position data into Airtable automatically. Test it until it works reliably across multiple runs. Then connect your primary bank account for transaction data.

You don't need every connection working on day one. Get two or three core connections running reliably and build from there. A partially automated dashboard with clean data in the connected sections is far more valuable than a fully planned dashboard with no live data.

Hours 16 to 24: Build the Notion Dashboard

Pull the key metrics from Airtable and lay them out in Notion in a way that gives you a clear picture at a glance. Use charts for trends, individual numbers for current state, and a simple traffic light color system (green, amber, red) to flag anything that needs attention. The goal is to look at this dashboard for five minutes on Monday morning and know exactly where you stand.

Hours 24 to 48: Set Up Alerts

In Make.com, create monitoring scenarios that check your key metrics on a schedule and send you a notification if something crosses a threshold. Position down more than 8%? Text message. Cash balance below your emergency fund floor? Email. Monthly expenses tracking 20% above budget with two weeks left in the month? Slack message. The alerts you set are a direct reflection of the risks you're actively managing.

Hours 48 to 72: Add the AI Analysis

Once your data is flowing cleanly, set up the weekly AI review in Galaxy.ai. Write specific, structured prompts. Vague questions get vague answers. "Analyze my portfolio" is useless. "Compare my portfolio return this month to the S&P 500 and identify the three largest contributors and detractors, then flag any positions where the weighting has changed by more than 2% from target allocation" is a question that produces actionable output. Reply with CLARITY and I'll send you the starting prompt pack I use for this weekly review.

What Actually Changes When You Can See Everything

I want to be direct with you: the dashboard doesn't make decisions for you. You still make the calls. What changes is the quality of information you're making those calls with, and the speed at which you notice when something needs your attention.

Before the dashboard, I made reactive decisions. A position would drop, I'd notice two weeks later during a manual review, and I'd make a semi-panicked call without the full context of what had happened in the intervening days. Now I see the move in real time, I review the surrounding context through my AI analysis, and I make a deliberate choice. Sometimes the right choice is to do nothing. But it's a conscious nothing , not an oversight.

The cash flow visibility has been the biggest personal unlock. When you see cash moving in and out of different entities in real time, you start seeing opportunities that were invisible before. Cash piling up in a business account that should be deployed into something productive. A tax liability coming in two months that you can start positioning for now. A rental property that looks underperforming on paper because you haven't correctly accounted for the equity accumulation behind the income statement numbers.

Information is not an edge in itself. But better information, applied consistently over time with clear frameworks for action , that compounds.

The Bottom Line

Most people have no real idea what their money is doing. They check a brokerage balance once a week and call it financial management. That's not management. That's observation with no feedback loop.

Build the dashboard. Get the full picture. Make decisions with real data instead of hunches, memory, and the vague anxiety that comes from not actually knowing.

The infrastructure takes time to set up. It pays for itself in the first month when it helps you catch one thing you would have missed. And in my experience, it always helps you catch something.

Alex Rivera

Wealth Architect at Wealth Grid