Honestly, I probably wouldn’t spend the $100K at all. I’d park it directly into our payment facilitation escrow pool to accelerate transaction liquidity and cash flow velocity across the platform.
Instead of waiting an average of ~3 days for settlement cycles, that capital lets us continuously recycle funds through order flow.
For example:
$50K in orders flows through the pool → becomes ~$100K available liquidity → grows to ~$150K as transactions compound → commissions are retained → ~$40K paid out → pool resets at a higher base (~$110K+) and continues compounding.
At scale, the value of faster settlement velocity and retained transaction flow is materially more important to us than burning capital on overhead. It directly strengthens the operating engine.
Dm Sent. 🏴☠️ Ridgerunner is exactly the kind of company that defines the next era of infrastructure. We’re not building another marketplace — we’re building the AI-native operating system and commerce infrastructure layer for the $900B+ outdoor industry.
Today, outdoor brands are fragmented across outdated tools, disconnected commerce systems, rising CACs, and generic marketplaces that don’t understand their customers. Ridgerunner gives brands an AI-powered platform to launch, operate, market, and scale — while simultaneously powering agentic product discovery and demand generation for consumers.
We already have 160+ live brands, 35,000+ SKUs, strategic distribution and demand partnerships reaching 100M+ consumers monthly, and a growing infrastructure stack spanning payments, fulfillment, AI onboarding, and conversational commerce.
We believe the next generation of software winners won’t just be SaaS dashboards — they’ll be intelligent infrastructure systems that operate entire industries. That’s what Ridgerunner is becoming.
We’re looking for partners who understand that AI-native commerce is not a feature layer. It’s a foundational shift in how businesses operate online.
@1752vc@damanchi Outdoor agentic infrastructure company with 150% MoM growth that’s in need of additional funding to fulfill POs - 100K works great here. Let’s chat?
I’ll check them out. - I know Eli Lilly has built an entire memory layer for themselves locally - architecture of this I have no idea. - I’m currently experimenting with building a memory layer using Obsidian and Ollama’s embedding llm so far it’s working well but the overall size is still fairly small
1000%
This may sound out there, but I think there’s a real case for the future of AI being local-first.
Instead of massive centralized data centers holding everyone’s data, imagine each person running their own private LLM locally — connected to external systems via OAuth, but with the actual data remaining fully segregated on-device.
Think Nvidia Jetson Nano-class hardware + 1–2TB local storage evolving into a personal AI appliance. Lower infrastructure costs, lower latency, better privacy, less dependence on hyperscalers, and users actually owning their intelligence layer.
The internet decentralized information. AI may decentralize full compute and memory next.
@thedlearner@brettcalhounn 3 bucks says they never respond - if they even review them. - my DM been setting for months, no open, no response. Good luck