Show IH: Built an AI sourcing copilot. 4 users, 3 are me. Need brutal feedback.
What it does: Infpilntr runs end-to-end product sourcing for Amazon FBA sellers — sends RFQs to multiple Alibaba suppliers in parallel, runs the actual back-and-forth negotiation (price, MOQ, terms), and calculates FBA landed cost (unit + freight + duty + FBA fees). 14-day free trial, no card, $39-$349/mo paid tiers.
Live: https://infpilntr.com
Pricing + ROI calculator: https://infpilntr.com/pricing
Stack: Next.js + Paddle + Cloudflare + a homegrown 9-LLM consensus engine I open-sourced separately
What's working:
- Product builds clean. RFQ batching + landed cost are the two features users actually use.
- Pricing page ROI calc converts well when people get there.
- Paddle handles all global payment/tax. Zero infrastructure pain.
What's not working:
- 4 users in a few months. 3 of them are me running test accounts.
- Cold launch. No marketing distribution. No founder-to-influencer relationships in FBA space.
- Helium 10 + Jungle Scout own brand mindshare. Sellers default to "does it integrate with H10?"
Brutal feedback I'm asking for:
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Naming: "Infpilntr" is hard to pronounce, harder to type. Should I rename pre-traction (cheap) or commit (hard later)?
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Wedge: Am I selling "AI sourcing copilot" (broad) or "Alibaba RFQ automation" (narrow)? My instinct says narrow but the homepage is broad.
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ICP: Solo FBA sellers ($39) vs small FBA agencies ($119-$349 with 3-10 seats)? The agency LTV is 5x but they take 3 weeks to onboard.
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The thing I might be wrong about: I think the moat is "the negotiation logic that gets MOQ down to 100 from 500." Helium 10 doesn't do this and probably won't because it's not adjacent to their core. But maybe the moat is just an LLM wrapping Alibaba's existing RFQ feature, in which case I'm cooked.
60-day commitment:
I'll post weekly metrics here. If I don't hit 25 paid by day 60, I'll publicly write up exactly what failed and why. Negative case is data the IH community can use.
Brutal welcome. Vague "looks good" not useful at this stage.
I know a couple of experienced Amazon FBA sellers who might be willing to answer your questions for free. Happy to forward them if you'd like, they're pretty sharp and could give you some good insights.
Renaming now is a low-cost refactor that prevents a major branding bottleneck before you hit scale. Focusing on the MOQ reduction as your primary wedge gives you a sharp advantage that data-heavy giants often overlook.
Are you planning to focus on agency outreach to hit your 25-user goal more efficiently?
The naming problem is bigger than the product problem right now.
Infpilntr is doing exactly what early B2B tools cannot afford:
making the buyer spend cognitive effort before trust even starts.
You’re asking FBA sellers to trust automation with supplier negotiation, margin math, and landed cost.
That already carries execution risk.
A hard-to-read, hard-to-say name adds unnecessary trust drag before they even test the product.
And in this category, that matters more than most founders think.
Because this is not “AI for sourcing.”
This is “let software negotiate with overseas suppliers on my behalf without screwing margin.”
That is not a novelty buy.
That is a trust buy.
Which means the wedge is not “AI sourcing copilot.”
That’s too broad, too generic, and sounds like another wrapper.
The real wedge is much tighter:
“Alibaba RFQ automation that cuts sourcing time and gets better MOQ/factory terms.”
That is specific.
That is legible.
That is easier to buy.
Right now the product may be sharper than the way it’s framed.
And yes, rename now.
Pre-traction is the cheapest point you’ll ever get to fix the trust layer.
If you keep building around supplier automation / sourcing intelligence, Exirra.com is materially stronger than Infpilntr here.
Cleaner.
More legible.
More software-shaped.
Much easier to trust in a workflow where margin mistakes are expensive.