Helioid’s Search Engine Provides Category Sorting To Aid Research, Targets Students And Professionals

The floor of Silicon Valley is littered with the carcasses of failed search startups. Without billions of dollars in resources like Microsoft or a tight vertical focus like travel site Kayak to help attract users, would-be competitors haven’t been able to pull people away from Google.

Helioid is a small startup out of New York that’s trying to change that, by delivering results tied to categories of information. It’s aiming at students, professionals and others who are trying to do exploratory research across a topic, and aren’t just looking for a specific answer to a question.

Its search results page shows a color-coded section on the left-hand side for the categories that it determines are most related to the search term. Each result has a dot next to it matching one of these categories, and a label showing the relative size of that category, with the most relevant ones at the top of the section.

If you click on any of the categories, you’ll add the category term as keywords to the search and generate a new, more focused set of results and related categories. You can keep doing this to generate increasingly focused results.

The overall advantage to the interface is that the categories reveal related areas to explore, that you might not easily identify on your own within the keyword-driven paradigm seen on the main pages of Google and Bing.

For example, let’s say I want to study up on popular types of fishing. A search for “fishing” shows me a set of relevant categories including “fly,” “salmon,” “saltwater,” etc. I click on “saltwater” and “deep is a top result. Adding that term then shows me a range of results about deep sea fishing.

Founder and chief executive Kenny Hamilton intends for Helioid to be a complement to general search engines, by helping specific types of professionals — journalists and bloggers (some of whom have started talking about it already), financial analysts, lawyers, etc. — get up to speed quickly on new topics. The business model is aimed in this direction, too. Beyond targeted search ads, he tells me that the company is looking at premium services for professionals, including private indexing for data that a particular user or organization is trying to analyze.

Helioid’s challenge in providing a general search tool is both to avoid making its product so complex that it cuts out potential users, and at the same time differentiate itself from Google in a way that users care about. Existing startups that are aiming to provide a better layer of organization to searches, like Blekko and its slashtags, face the same sorts of problems. Googles’ “Related searches” page is stiff competition.

But, while I’m not sure how well Helioid will be able to penetrate its target market, the interface is intuitive, and I found it useful for topic exploration in testing.

Hamilton and his cofounder, Peter Lubell-Doughtie, met while getting undergraduate degrees at Stanford (physics and symbolic systems, respectively). Hamilton has been building Helioid for the last few years, while Lubell-Doughtie has been working on it part-time while he finished a graduate degree in artificial intelligence at the University of Amsterdam. They haven’t taken funding.