EagleMapThe buyingoperation where AI runs every vendor.
8-figure run-rate. A small in-house team. Bootstrapped. EagleMap is the in-house buying operation behind SUPERSONICBRICK.AI's 50+ vendor relationships — agents draft, the buyers approve.
Picking profitable SKUs from a 50+ wholesaler catalog used to be a months-long human exercise. A 2M+ SKU shelf is now screened in hours and the winners route themselves to listing.
per operator.
100+ markdown SOPs in a repo. Agents pick them up and run scraping, screening, listing and pricing — 24/7, resumable, self-healing.
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“In the AI agent era, we don't hire operators anymore. We write the SOP in markdown and the AI agents run the company.”
Vertical ecom, end-to-end on agents.
An AI agent fleet on top of an in-house orchestration runtime — covering every link of the ecom value chain. Selection, vision matching, copy + visuals, ROI gating, QuickBooks reconciliation, vendor POs, supplier tracking. All integrated. All in production.
Catalog to confirmed, in eight numbered steps.
Each row is photographed by Llama 4 Vision, label-read against the Amazon listing, priced by Keepa, and verdicted by Claude — without a hand on the wheel.
Read the photo. Find the ASIN. Score the ROI.
Llama 4 Vision reads each wholesaler photo and writes the Amazon search terms. Gemini second-passes the match to cut visual false positives. Keepa supplies sales rank and price history. Claude scores margin, brand risk and gate. What survives is a confirmed product — ready to list.
Ten people. Eight figures.
A ten-person team running an eight-figure ecom operation — humans make the calls, agents do the work, twenty-four seven.
OpenClawClauderunning OpenClaw·no SaaS bill, no agency — the stack is the teamFour models. One pipeline.
OpenClaw dispatches work. Claude reasons over the catalog. Llama 4 Vision reads the photos. Gemini verifies the match and ships the visuals. Every output passes through a human approval gate before it touches the catalog or the books.
Picks up markdown SOPs from the repo, dispatches scrapes, ETLs, listing pushes — and reconciles back into the catalog.
Reads margins, BuyBox history, brand risk and seller competition. Decides, per SKU, whether it earns a shelf.
Reads each product photo, writes the Amazon search terms and category. The unlock for UPC→ASIN at scale.
Second-passes Llama 4 matches against the Amazon photo. Then renders A+ visuals and use-case images via Nano Banana.
Fifty wholesalers. One buying relationship.
Grocery, hardware, beauty, electrical, pet, medical — each vendor on its own portal, its own schema, its own login. EagleMap normalizes them into one buying surface for our category buyers.
Built to behave like a polite logged-in buyer on each vendor portal — rate-limited, session-aware, respects each vendor's caching and concurrency limits.
Long catalog walks checkpoint every batch so a dropped session never costs the vendor a re-pull. Concurrency is tuned per-vendor to stay inside each portal's published limits.
Where a vendor publishes a buyer-facing data feed we use that path and fall back to standard portal browse where they don't — fewer requests, lighter load on the vendor's stack.
50+ vendor relationships. Recurring POs since 2023.
We're a buyer, not a browser. SUPERSONICBRICK.AI is an active buyer on 50+ wholesale accounts, with long-standing relationships across our active categories. Weekly POs, QuickBooks-reconciled payments, every account has a dedicated point of contact — on your AR aging report, and on time. The longest-running of these relationships pre-date the AI layer entirely — we shipped weekly POs before the agents could write them.
Big buys. On a clock.
For wholesalers that lands as very large POs — and the same POs back next cycle, not a one-time spike. Our buying engine sizes depth from real downstream demand and rebuilds the buy list on a weekly cycle, so the buy is large by design and recurring by clock.
Brand-policy first. Listing-quality enforced before takedown.
We don't list brands we're not authorized or qualified to resell. MAP, authorized-seller and listing-quality policies are enforced inside the listing pipeline — before a SKU goes live, not after a takedown notice arrives.
Eight storefronts, one ledger.
Sales, orders, inventory and listing health — synced across eight storefronts on six marketplaces. Per-marketplace analytics stay inside the team; vendor-level reporting is shared on request.
Inventory and orders, live across eight storefronts
A single console for listings, FBA/FBM stock and price sync — reconciled against the catalog and the agents that maintain it.
Every confirmed product, watched continuously
BuyBox, payout, supplier cost, rank and ROI — refreshed from the Keepa cache without leaving the desk.
Fifty-plus wholesalers, scraped and scored
From Home Depot to Ferguson — SKU coverage, UPC fill-rate, ASIN hit rate and top brands per vendor, summarized by agents.
The numbers speak for themselves.
No pitch deck. No slideware. The catalog, the storefronts, the run-rate — all running in production, today.
Every function, AI native.
EagleMap isn't a tool with an AI feature bolted on. Ten organs run the workspace — each one model-driven, agent-orchestrated, and wired into the same catalog.
Outreach, brands, books — same console.
Five thousand distributors profiled, scored for fit by Claude, and queued into sequenced outreach by OpenClaw.
Every catalog brand mapped to category market share, seller competition and rank history — pulled into one console.
Two operating companies reconciled into one ledger. Sales, fees, refunds, payouts — synced from each storefront.
The brains and the rails behind it.
Three models reason; three platforms keep the rest honest.
Sourcing, listing, pricing, books. One in-house system across six marketplaces and eight storefronts — run by agents, written in markdown.