Watch it find
what you can't see.
Pick the business that looks most like yours. We take a pile of the ordinary data it already has, run it through Polygon™, and surface the one decision sitting in plain sight.
Both companies below are invented. The data, and the blind spots, are the kind we find in almost every set of books we open.
A distributor of industrial pumps, valves, fittings, and spare parts to Gulf Coast plants and contractors. Solid business, steady customers, a name people in the region know.
Nothing exotic. The same files sitting on any distributor's shared drive.
Polygon reads all of it at once, ties every freight charge and discount back to the line it belongs to, and builds one clean picture. No data left the company's environment.
The biggest line is the weakest earner.
By revenue, Process Equipment is the clear leader. Then you account for the freight on heavy gear and the volume discounts sales gives away to win those big orders. The picture inverts.
Starved on what sells. Buried in what doesn't.
The inventory tells the same story from the other side. Capital is locked in parts that haven't moved in a year, while the fast movers keep running out.
Margin after landed cost, by line. Revenue was on every report. The freight and discounts that eat it were not.
How fast each part actually turns. Reorders ran on gut, not on velocity.
A dead-stock review. Nothing flagged the parts quietly sitting for a year.
None of this is hard to track. It just wasn't.
- → Re-price or renegotiate freight on the high-volume line so the biggest seller stops being the smallest earner.
- → Clear the dead stock and move that capital back into parts that turn.
- → Set reorder points by velocity so the fast movers stop selling out.
And we built it to keep watching.
We didn't stop at the finding. Powered Metrics published a small AI integration straight into Calcasieu's own data landscape. Every new month of sales, inventory, and freight data runs through it automatically.
- A product line's margin slipping once freight and discounts are counted
- Parts crossing into dead-stock territory
- Fast movers trending toward a stockout
The one-time finding becomes a standing early warning. Your team still makes the calls. The integration just makes sure the right things reach the desk in time.
A fabrication and machine shop serving industrial clients across the region. Good people, good work, a reputation that keeps the bays full.
The records every shop already keeps.
Polygon lines up revenue, customers, and payment timing into one view, then looks at how each thread moves over time. The trend is where the story was hiding.
The best year is hiding a slow leak.
Total revenue is climbing, exactly as the owner sees it. But almost all of it leans on two accounts, and the biggest one has been shrinking for three quarters while everything else covered the gap.
The biggest risk is also the slowest to pay.
The same anchor customer has been stretching its terms. The exposure and the cash squeeze are sitting in one account.
Customer concentration. How much of the business rests on the top one or two accounts.
Revenue trend per customer. Not just the total, but which way each account is moving.
Days to pay, by customer. Where the cash is slow and the risk is stacking up.
Standard things to watch. None of them were on a report.
- → Start filling the pipeline now, while the shop is strong and has leverage, not after the decline shows up in the bank balance.
- → Have the direct conversation with the anchor customer, early enough to change the trajectory.
- → Tighten terms on the slow-paying account.
Next time, it surfaces in the first quarter.
We didn't stop at the finding here either. Powered Metrics published an AI integration into Delta's data landscape that runs on every new batch of invoices and jobs, on its own.
- Any single account climbing toward dangerous concentration
- A major customer's revenue starting to slide
- Days-to-pay stretching on a key account
The blind spot that took three quarters to surface would now surface in the first. The owner still decides what to do. The integration makes sure he sees it coming.
Both companies are invented. The blind spots are not. We find versions of these in almost every set of books we open, because the answer is usually already in the data, just not in a form anyone can act on. That is the whole job.