Datafox offers optimized solutions for investors to screen startups

Absrtact: Datafox, a start-up company based in Silicon Valley, provides a real-time update database for unlisted companies, trying to solve a few problems for investors: where to collect startup data, what data to collect, and how to

Datafox, a start-up company based in Silicon Valley, provides a real-time update database for unlisted companies, trying to solve a few of the problems for investors: where to collect startup data, what data to collect, and how to ensure that the data collected is very new and complete.

Co-founder Bastiaan and Mike Dorsey are both financially born. Why go to the technology field to start a business? "Because of my own previous three years at Goldman Sachs, there has been a very troubling thing about how to search for information on small and ESSG enterprises." "Bastiaan told 36 Krypton:" Many colleagues in the actual work are very distressed, I feel very need to solve this problem. ”

The basic function of Datafox is to automate the acquisition of useful data from two channels:

searches for network information and finds valuable parts through semantic analysis algorithms. Work with Crunchbase, AngelList and LinkedIn to get data directly from the three databases with lots of startups. What users want to do is search for interested companies, click on attention, or track the list of industries that others share, such as social networking and robotics.

In Datafox's homepage, will see the new Business Circle event, the content is datafox according to the user concern company customization. You can also choose the types of events, including financing, acquisitions, IPOs, valuations, revenue, talent, and news coverage.

In the company search interface, the results can be filtered by various conditions, such as operation, industry, location, investor, number of employees, financial status, financing stage, etc. In addition to the traditional information, the company interface also has an associated LinkedIn option to facilitate direct contact with the company.

In addition to the basic data acquisition, there are two well worth mentioning plus:

The first is the Datafox Quality score™, which is a comprehensive score based on a proprietary algorithm to evaluate startups in real time, with a breakdown of corporate growth scores and HR manpower scores. At present they use more than 20 parameters, including recruitment speed and direction, retention rate, founder background, board quality, investor quality, financing quantity, user evaluation, social network activity, as well as other network analysis indicators. The other is relational visualization. If you want to know the relationship of a company in the market with other similar companies in terms of similarity, income, financing or number of employees, you can click the Visualize button and Datafox will show you a simple and intuitive network map. In this chart, you can connect to the company's position in the industry, potential investors, who is the future partner, who is the potential threat, who may buy the company, etc.

At present, there are three kinds of real-time data sources in Datafox. One is public information, such as news, RSS feeds, YouTube, and so on. The other is existing databases, such as Crunchbase, AngelList, and LinkedIn. The last one is Datafox's own data analysis, such as the network Diagram mentioned earlier. Datafox data is more automatic and almost real-time than traditional databases.

Datafox Target Users In addition to investors, as well as analysts, sales and so on. This charge mode is monthly subscription type: Novice Monthly $49,100 Company, 3 areas, professional users monthly $399, no restrictions, enterprise-class will provide APIs to facilitate integration with other applications or custom development.

Like many startups on this side of the Bay Area, the core team of four co-founders is exclusively's Stanford background. Bastiaan Janmat A three-year investment-related job at Goldman Sachs in London, and Mike Dorsey has a master's degree in MBA and engineering. Products on the line to get Google Venture 1.8 million U.S. dollars seed wheel, and then StartX, innospring and other Silicon Valley local incubator, including 17 of its second round of seed fund investment. The venture's unanimous focus is on a new solution for investors to search for startups.

The following is Bastiaan received 36 Krypton interview content, I feel he and the product itself is like a agile but very sincere fox, sorted as follows:

I have a headache. There is no efficient way to search for unlisted companies, including many startups. Talking to a lot of Wall Street friends, they also tell me that there is a clear fact that more and more companies are opting for private and temporary unlisted. Finding information about these companies is difficult, and we need to manually search for that information and put it in the form, which is cumbersome, so I've been looking for ways to automate.

Datafox is an amateur project for several of us. When it was shown to some financiers and to the Silicon Valley VCs, they all said Datafox could help them save a lot of time, so we quickly got the seed wheel of Google venture.

Over the past 10-15 years, the work of analysts, sales and VCs has been simple for the reasons of the network, but the network has also brought information noise. So I think what they need is a tool on top of the data to collect and filter out the key information. Datafox is a tool with data aggregation, cleanup, feature extraction, semantic processing, and so on, telling users what companies he's interested in doing something that he might be more interested in.

We hope to find a formula that can accurately evaluate the operation of the company by collecting a lot of data and combining industry knowledge and machine learning. This is a bit like the market index or Google's PageRank, which marks the relative level of a company in an industry.

From the perspective of investors, we try to cover all the data that a company can use for potential investors, such as team, finance, customer, partnership, media coverage, and so on. We also think in terms of sales and business development, because they can find out whether a company has strong potential. Datafox data covers a wide range, analogy crunchbase mainly focus on financing numbers, we will provide a complete picture.

Frankly speaking, we also have some problems at present. For example, the law does not stipulate that private enterprises must report and disclose company information, so Datafox cannot guarantee the absolute integrity of information. What we can do is collect and integrate the public information scattered throughout the network, and then present it to the users after their own algorithms. Currently Datafox allows users to report objectionable data, we intend to introduce more effective methods like confidence indices in the future to help users make decisions.

We currently use more than 20 features. including retention rate, founder background, board of directors, investors, financing, user evaluation, etc. The score range is 0 to 1250, the higher the better, the closer the description is to the "successful" company we define.

We want to be the analytic layer above the original data. Later we intend to allow users to add additional data sources to their Datafox accounts, and then we will help analyze and visualize those data. Forms may include analytical tools and research reports.

When I was at Goldman Sachs, I was very envious of the people who were doing business. They have rich management and operational experience, and can make great products and services. That's one of the reasons I came to Stanford to read an MBA. What I do at Goldman Sachs is investment-related work, and now I'm doing a product that serves investors. I think the background has helped me a lot in doing this. When you start a business, you feel like you have the whole company, and you have a lot of responsibility, and you get a strong emotional impact when you work together to achieve a goal.

I certainly intend to expand to China later, but unfortunately it is too difficult in a short time. We first have to solve the language problem, the semantic processing of Chinese is a challenge to our technical team. In addition to China's complex business environment, we need to know more about it. In the future, we certainly want to be able to expand internationally, but at present we will only focus on American companies.