LM Studio
Ollama
GPT4All
Jan.ai
AnythingLLM
ChatGPT
llama.cpp
Claude AI
StackScan
BuiltWith
Wappalyzer
W3Techs
TheirStack
WhatRuns
Hunter.io
ZoomInfo
StackScan helps businesses find and analyze websites based on the technologies they use or the keywords they target. Instead of manually researching websites one by one, users can instantly search across 100M+ domains and identify sites using platforms like Shopify, WordPress, WooCommerce, Webflow, and thousands of other technologies.
The platform provides practical filtering tools that allow users to narrow results by country, TLD, industry, or specific technology combinations. This makes it useful for building targeted lead lists, researching competitors, discovering niche markets, or identifying companies using certain software stacks for outreach and partnerships.
StackScan also supports bulk data downloads, keyword-based website discovery, and structured reporting to simplify large-scale research workflows. With continuously refreshed datasets and scalable search capabilities, it enables marketers, agencies, analysts, and growth teams to access actionable web intelligence quickly and efficiently.
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StackScan's answer:
StackScan focuses on practical usability, broader stack coverage, advanced filtering, and scalable exports without unnecessary complexity. Users can quickly generate highly targeted datasets using filters like country, TLD, industry, and technology combinations, making research and lead generation faster and more precise.
StackScan's answer:
StackScan combines technology stack discovery and keyword-intent research in a single platform, allowing users to find websites not only by the tools they use but also by what they are targeting online. With coverage across 50,000+ technologies and 100M+ domains, it provides scalable, filterable, and export-ready web intelligence.
StackScan's answer:
StackScan is built for marketers, growth teams, agencies, sales teams, analysts, SaaS companies, and researchers who need structured web intelligence for prospecting, competitor analysis, market research, or technology adoption tracking.
StackScan's answer:
StackScan was created to simplify the process of finding reliable website and technology data at scale. Existing solutions often felt limited, expensive, or difficult to use for targeted workflows, so StackScan was built as a practical and scalable platform that combines technology detection, keyword discovery, and bulk data access into one system.
StackScan's answer:
StackScan is built using modern web technologies, large-scale crawling systems, distributed data processing, and technology fingerprinting engines designed to analyze and structure massive amounts of web data efficiently.
StackScan's answer:
StackScan is used by agencies, SaaS businesses, growth teams, researchers, and data-driven organizations for lead generation, market intelligence, and competitive analysis across multiple industries.
While itโs still in early stage, its lifetime deal is really a great value. Must get if youโre into lead generation.
Based on our record, LM Studio seems to be more popular. It has been mentiond 58 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I use Bionic (https://lmstudio.ai) and various local models like Qwen Coder Next to work on various tasks. Honestly, none of the models that are runnable on a typical MacBook Pro come close to the cloud-based frontier models (open or closed) but Bionic provides a nice experience and makes trying new models out trivial. - Source: Hacker News / 11 days ago
They hid it well at the bottom of the page: https://lmstudio.ai/. - Source: Hacker News / about 1 month ago
A good place to browse is the LocalLLaMa subreddit. [0] A good software to start is LM Studio [1]. Another popular alternative is Ollama [2]. A better software when you're used to it all is llama.cpp as it's usually a bit faster and more frequently updated [3]. A good place to get models is HuggingFace, particularly the Unsloth models [4] Most popular models lately to run on "regular" gaming PC's, workstations,... - Source: Hacker News / about 2 months ago
LM Studio wraps the same inference engine in a desktop application with a visual model browser, one-click downloads from Hugging Face, and a built-in chat interface. - Source: dev.to / 2 months ago
LM Studio is the reference standard for running local models. It's not really an "AI client" in the workspace sense โ it's a local inference engine with a chat UI attached. Its MLX backend on Apple Silicon is noticeably faster than Ollama for many models, especially on larger ones, though both now use MLX on Mac so the gap has narrowed over time. The built-in model browser lets you discover, download, and run... - Source: dev.to / 2 months ago
Ollama - The easiest way to run large language models locally
BuiltWith - Find out the technology behind websites
GPT4All - A powerful assistant chatbot that you can run on your laptop
Wappalyzer - Wappalyzer is a technology profilers and leads data provider. Create lists of websites and contacts that use certain technologies.
Jan.ai - Run LLMs like Mistral or Llama2 locally and offline on your computer, or connect to remote AI APIs like OpenAIโs GPT-4 or Groq.
W3Techs - W3Techs provides information about the usage of various types of technologies on the web.