Shareloc
Tells you where to open your next location. And exactly why.
What it does
Shareloc helps retail and hospitality expansion teams make smarter location decisions - before signing a lease. Pick any vacant listing and get an instant AI score across five dimensions: footfall, permit fit, affordability, competition, and concept gap. Then compare locations side by side, and get a clear recommendation - not just data. Get clear answers to: → Which location is better and why? → Where to expand next? Running pilots now across the Netherlands. Try it free at shareloc.io.
Does the same job
all alternatives →- AWA website that heatmaps your city based on your housing preferences2025 · theretowhere.com · ▲321
For the past few months, I've been working on a website that answers two different questions: - Where in my city have the best travel times to all the things and people I care about? - Given a listing, how far is it from all the things and people I care about? Personally this was fueled by my own frustrations when I was apartment hunting in NYC. I was frustrating to have to juggle so many Google Maps tabs when I was evaluating a listing, and it was also annoying to not have full confidence that I was even searching in the right places. I wanted to be close to work, a Trader Joe's, and a…
- TPThe pitch deck we're raising $800k with2015 · localizejs.com · ▲17
I believe strongly that information should be shared as freely as possible. This is one of the big reasons I started Localize, to make it an order of magnitude easier for information or knowledge to transfer from person to person, despite a difference in language. On openness, we've decided to share things companies normally don't share. We're starting with the pitch deck we're using to pitch investors for a $800k seed round we just started raising, plus snippets of our traction and growth charts. Why do this? The more we share, the more exposure other people have to our work. If our work is…
- WDWhereHop, data-driven travel recommendations2017 · ▲7
Hi guys, wanted to show my (few) weekends project: http://wherehop.com A free app for you to basically see the best neighbourhoods to live in in many cities around the world. It uses data pulled from various sources to rank the best areas to live. Let me know your thoughts and how it can be improved.
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
Launched alongside, May 2026
the whole month →
Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
- NW
Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com
- FM
Dev tools · May 2026 · github.com