PHOS AI Labs· AI consulting firm
Phos AI Labs is the embedded AI strategy and operations for serious companies ($5M–$25M). The strategy first, then the systems; in the right order.
What is PHOS AI Labs?
PHOS AI Labs is an AI consulting firm.
Phos AI Labs is the embedded AI Lab for serious companies ($5M–$25M). We spend two weeks understanding your business before we build anything; we stay in the room long after the first systems go live. Every system we install makes the next one faster, more specific, and more defensible. 400+ engagements across manufacturing, aviation, distribution, professional services, and healthcare; clients including Zapier, Coca-Cola, Medtronic, and American Express.
Phos AI Labs is the embedded AI Lab for serious companies ($5M–$25M). We spend two weeks understanding your business before we build anything; we stay in the room long after the first systems go live. Every system we install makes the next one faster, more specific, and more defensible. 400+ engagements across manufacturing, aviation, distribution, professional services, and healthcare; clients including Zapier, Coca-Cola, Medtronic, and American Express.
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FounderPlaybooks.
What other founders did to grow.
2722 dispatches from hundreds of founders, pulled from the week's best podcasts.
I personally offer purchasing power parity pricing for almost all my products which adjusts the prices based on the financial stability and purchasing power in a country compared to where it's being sold from and this method helps people afford your product who otherwise couldn't
Default to purchasing-power-parity pricing
Set PPP pricing across your entire catalog, not just the flagship — auto-adjust checkout prices to the buyer's country relative to your home market. The per-sale revenue dip is more than offset by the volume of buyers who simply couldn't transact at the flat price. Use a Gumroad/Lemon Squeezy-style PPP plugin, set it once, and forget it.
one of them is incrementality so you want to switch ads on switch ads off and see what's happening to your baseline which is always of course a good position for smaller developers if you don't have a ton of organic yet
Use incrementality testing — switch ads on and off to isolate channel impact without a data science team
Before building data science infrastructure, Burke validates channel ROI using a simple incrementality check: pause spend for a period and observe baseline installs and trials. If they drop materially, the channel was contributing. This works especially well for early-stage apps with limited organic that can cleanly isolate the ad effect.
There's a play for whatever you're stuck on.
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