SQL Chat VS Huntli

Huntli's answer:

Most shopping tools stop at putting a photo and a price next to a recommendation. Huntli does the research behind it: it reads the spec sheet, the reviews and owner forums, checks live prices at the shop, flags invented "was" prices, and scores every product against a fixed rubric for its category. For multi-part purchases like a PC build, it checks every part against the rest and tracks the budget.

Huntli's answer:

Shoppers making purchases worth getting right: headphones, a laptop, a PC build, a home-studio setup. People who would otherwise open forty browser tabs and start a spreadsheet, and people who just want a trustworthy answer without doing that.

Huntli's answer:

Huntli started as a spreadsheet. I made one for every big decision, and when I started shopping with AI, the recommendations were good but arrived as plain text. Checking what each item looked like, who sold it and whether it was any good still meant dozens of tabs and copying specs by hand. Huntli began by putting the real product next to the recommendation, then kept digging into spec sheets, reviews and forum threads. The Stash is that spreadsheet, automated. The hound in the logo is Alfie, the family dog.

Huntli's answer:

Next.js and React on Vercel, Supabase (Postgres, auth and edge functions), Tailwind CSS, and current large language models for research and analysis (Google Gemini today).

Huntli's answer:

Huntli runs on the same kind of AI as ChatGPT, Perplexity, Gemini or Meta's Muse: current large language models searching the live web. What differs is what's built around them. A chat leaves you an answer in a transcript. Huntli leaves you a Stash: every candidate priced live at the shop, fake "was" prices flagged, each product scored against a fixed rubric for its category and, for a build, every part checked against the rest. Share it and the other person sees it as it stands now; leave it and price-drop alerts keep watching. Muse can check out for you; Huntli stops at the decision. Price trackers like Keepa follow a product you've already picked, and coupon extensions like Honey step in at checkout. Huntli works earlier, on deciding what to buy. Free, no ads, no sponsored ranking, nothing to install.

Huntli's answer:

• Individual shoppers: Huntli is built for consumers, not businesses, and is free to use
• PC builders who need every part checked against the rest of the build and the budget
• People kitting out a home studio or a smart home, where parts have to work together
• Anyone making a purchase worth getting right: headphones, laptops, cameras, appliances
• Deal-checkers who want to know whether a "sale" price is a real discount
• Couples, families and friends who share a Stash to decide on a purchase together
• Shoppers in the US, UK, Canada, Australia and 11 more European countries