Semantic Juice


Build a custom search engine in minutes with Semantic Juice. A topical crawling service for online professionals, it allows you to analyze a specific niche with features such as competitor analysis, keyword research, competitor analysis, and backlink tracking.
Semantic Juice SEO Software is a powerful tool for developers. It allows you to access data on niche websites such as content or images, and create reports defined by topics, domains, crawling intervals, URL paths, and more. Designed to help you detect crawl trends in real-time, this innovative software will help you build cool websites supported with relevant data.

Build a custom search engine in minutes or analyze a specific niche with our topical crawling service.

Example vertical search engines

Controversial topics

Find issues people debate passionately about.

Explore architecural studios, magazines, awards.

Search Engine Optimization
See and compare top results from small sample.
Configurable Crawling Jobs
You can define topics, domains, url paths, regular expression, crawling intervals, general, seed, and news crawling modes. Built-in features make our crawlers more efficient as they ignore near duplicate content, spam pages, link farms, and have a real time domain relevancy algoritm which gets you the most relevant content for your topic.

Our backlink and SEO queries can help you detect crawl trends and update crawl settings in real time.
Machine Learning
Provide a few quality example links from different web-sites to teach our system what topic to crawl. Topic, as understood by the machine, is defined by word combinations found in pages, and is language independent. Quick SEO mode get these example links for the given phrase from major search engines.

For example, if you provide pages about a single person or location, that name will NOT be the only hint for the machine, but word statistics will also detect other significant concepts, and results will contain pages that do not relate to that person or location only. Similarly, our algorithm neither detects a ‘style’ of writing nor finds all literary works of an author. Technically this can be done, but requires different machine learning approach.