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Product research for shoppers: live prices at verified retailers, compatibility checks across whole builds, and Stashes with price-drop alerts and AI insights.

The modern platform for creating, sharing, and collaborating on AI prompts. Advanced version control and real-time testing.

Website, pricing, platforms and company facts side by side.
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| Website | huntli.app | diffyn.com |
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| Company | Startup from The Netherlands · 1 - 9 employees · 2026 | — |
| Listed in |
In their own words, as submitted to SaaSHub.


Huntli is an AI research agent for shoppers, built for the part of buying that search engines handle badly: the research. Describe what you need in plain language, such as "noise-cancelling headphones for an open-plan office, under €400, comfortable all day", and Huntli works the problem. It...
No description of Diffyn yet.
What each product offers, as listed by its team.


An editorial look at what each product does well and who it suits.


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The Ultimate Prompt Tool for Creators – Visualize & Organize with Diffyn
How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing Huntli and Diffyn.
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.
Diffyn's answer:
Addresses workflow and change management on LLM prompts, provide teams with traceability and visualization of tests across multiple models, provide deeper understading into efficiency of these prompts.
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.
Diffyn's answer:
Diffyn is the platform that specializes on both change management and multi-model analysis.
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).
Diffyn's answer:
React, Next.js, POSTGRESQL
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.
Diffyn's answer:
Professionals incorporating LLMs or AI tools in their workflow and wants to keep track of changes and test their prompts.
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.
Diffyn's answer:
I started working on Diffyn when I notice that prompting has become an essential part of work across many industries. While there are version control platofrms like github, they are not designed for just prompt management are can be overkill such applications, it is also not integrated natively with various LLMs and relevant tools for users to validate ideas and visualise results properly.
Huntli's answer
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