Introducing Nigel: The First and Only AI Company Analysis Bot
Say Hi to Nigel, your new digital company analyst.
Nigel is much more than a friendly A.I. bot; he’s a smart friend that will challenge the way you consume and digest information about companies. Whether it is a Silicon Valley unicorn, a boutique fashion e-commerce retailer in New York or a London-based biotech startup that keeps a low profile — Nigel knows the answer.
After years of research and development, we at Zirra are thrilled to launch Nigel — the future of company analysis. Nigel responds to complicated analysis questions such as “who are Uber’s closest competitors” or “who exactly is Lyft hiring.” Nigel provides you with intelligent insights and facts about companies, saving hours of research.
Whilst other A.I. bots will retrieve facts, Nigel gathers human-like insights, like no other virtual assistant has achieved before in the entire history of bots.
Nigel can calculate the level of competition between companies, come up with valuations, tell how strong a management team is, and evaluate risk and success factors for any company being asked about. Go ahead, just ask him questions in plain and intuitive English about any company — he will instantly reply to you within seconds.
How is Nigel saving you time and hassle? He is the product of a multi-year effort in research and development of a unique NLP technology, processing unstructured information from about 85 data-sources such as incoming company traffic, social media links, user reviews and media mentions, sorting out conflicting information, continuously calibrating each bit of information with a database of more than 2,000 already analyzed companies. In short, Nigel performs all the smart footwork you would need in order to actually know a company.
We added some extra effort in polishing Nigel’s English comprehension ability so that he will be able to accept free, plain, everyday English in many variations.
Since we already presented Nigel as a friendly analyst, we can also disclose that he knows how to listen. He absorbs feedback, calibrates his calculating skills, and make corrections when confronted.
Nigel is a happy bot, surrounded by his family: his cradle of birth is Zirra, a tech company that has developed A.I. and Machine Learning capabilities to effectively analyze public and private companies, using dozens of overt data sources. Zirra is already serving dozens of investors, using its technology to produce hundreds of company research reports.
Nigel, however, will appeal to a vast audience of researchers, analysts, and enterprise executives, practically everyone that is interested in instant information on any company.
Nigel can already see in his cloud-based imagination how he helps investors scouting candidates or analyzing a company for investment, candidates curious about a job opportunity, sales executives looking for the right contact, and service providers looking for the proper inroad to a company.
Now let’s go back to Nigel, who can perform two major sorts of tasks: retrieve information on companies and come up with insights on them. Let’s begin with the information retrieving part:
Our CTO David Hessing recorded himself analyzing 3 companies in under 10 minutes using the Zirra A.I. Bot. Watch how he did it
Company Facts by Nigel
The Basic Facts
@nigel, give me basic facts about Lyft
Asking Nigel for “basic facts about” any company will instantly retrieve the requested company’s year of foundation, location, office contact details, sector, industry, sub industry, previous company names and the complete list of social network accounts and other database profile of the company such as LinkedIn, Facebook, Twitter, Instagram, Bloomberg and CrunchBase.
@nigel, can I get company descriptions for Udacity
Asking Nigel for “Descriptions about” any company, brings a variety of descriptions from a variety of web sources. Some of these descriptions are linked to their original web page, allowing further research.
@nigel get the funding history of Uber
Asking Nigel for the “funding history for” a company retrieves its entire funding history of a including the total amount raised, number of round, a list investors, date of investment, for each round separately.
@nigel, who is in the management team of Wework?
Asking Nigel “who is the management team of” a company or “who are the managers of” a company, or “Can I see management for X”, will show a list of the top management, with up to top managers in each company. For each, Nigel will retrieve name, role, and a list of social profiles, such as LinkedIn, Twitter, Facebook, CrunchBase, Angel.co, and Bloomberg, related to the person.
Hey, @nigel, is Blue Apron hiring?
Checking out a company’s open positions list can give a sense of the company’s scale of growth and the direction in which it chooses to go at the moment: sales and marketing, engineering, operation, senior management or human resources. By typing “open position in” a company, or “Is X hiring?” Nigel will pull out a summarized list of open positions with embedded links, allowing the user to get the full picture of each position in its original site of publication.
Job seekers will be able to look for new positions in companies they find interesting by typing their names, and then use the links to read the full job description and apply for the job.
IP and Trademarks
@nigel, show me IP information
Well, the last bit of information might be the most important. After all, the valuation of a startup differs very much depending on whether it has IP in its bag. By typing “Show me IP/ patent information on” a company, Nigel will come up with a list that contains the total number of patents and trademarks, sorted by year. Nigel knows to conclude when and how many of the patents or trademarks were just filed, are pending, or were already granted.
At this stage Nigel checks for number of patents and trademarks, and we’re working hard to list them in the future.
Company Insights by Nigel
After going through facts about searched companies that can be retrieved, it is now the time to move on to the fun part of asking Nigel for eye-opening insights. Yes, Nigel is a smart butler, not just a simple bot that collects data, but one that draws conclusions about what does the data mean.
@nigel, show me web traffic for Airbnb
You can now get an instant look at the daily web traffic for any service just by typing “traffic of” or “traffic for” a company. Nigel also allows comparing between the traffic of up to four companies at once. For instance, click “traffic of Airbnb”, or “traffic of Airbnb, Hilton” for comparing the two. To our knowledge, this is the fastest, simplest way to get a look at a company’s mobile and desktop traffic today. To our humble opinion, it is also a fun way to get a look at a company’s momentum.
@nigel show me newsfeed for SpaceX
Zirra’s unique NLP algorithms scan the media and ingest thousands of articles everyday to spot meaningful events in a company’s history. This is a brand new way to get the important news on any company of interest. We find the relevant companies in those articles, link them to those companies, using our own entity recognition techniques. By typing “show me news feed for” a company, Nigel will retrieve a dozen news-related events, embedded with links to the original news website or blog they were published in.
In case other companies are mentioned in these news articles, the articles will be linked to those companies as well.
@nigel show latest events for Coursera
Searching for news with Nigel or on Google News brings quite a lot data, but Nigel’s Meaningful Events module brings you the essence, limiting Meaningful events to financial rounds, mergers and acquisitions, product launches, partnership announcements, management changes, office changes, legal issues, bankruptcies, or an investment in another company. This can be done by asking Nigel to “Show me events for” a company (“Nigel, show me events for Coursera”). The result is a list of events, and for each of them the list of links it is mentioned in.
These events are also visible in Zirra’s homepage, whereas searching a company will produce an automated profile of it. Right now we’re using primarily NLP-based pattern matching techniques to find those meaningful events, but over the next few months we’ll be adding probabilistic NLP techniques to find events, so we’re still working on ways to make it even much better.
@nigel, find me competitors for Outbrain
Nigel also take these articles, and besides finding events in them it put them all into a large NLP module that close out all the semantic relationship between companies, and it can look at the resulting model to find companies that are close to each other, which usually means that they are competitors.
Typing “show me competitors for” a company, will result in a list of companies rated from zero to one. This indicates how those companies are close to each other on the multi-dimensional semantic model. Scores of above 0.5 are almost always direct competitors, while score of 0.3–0.5 tells about some relationship, although often it is a mild competition.
This technology is also already implemented in Zirra’s automatic report on our website. The results are being improved with time, as the site allows for human suggestions, being overlaid on the model to tweak it enhanced and provided feedback. With human feedback, The NLP modules will become more robust in the following months.
Team, Momentum, and Product Ratings
@nigel, show me ratings for Dropbox
Nigel is not only able to bring you objective information, but also tell you his personal opinion of the company. On a scale of 1–10, Nigel can rate each company’s management team, momentum, product, opportunity, vision and execution.
These ratings are a product of Zirra’s own model. We assembled about 2,000 companies, curated them and scored. On that basis, we created a regression comparative-type model, so that we can look at any company against that set and see where it sits.
Basically, it is the first time someone built a commercial model of successful companies that is used as a benchmark for any new company in the market. This model is being crafted and constantly improved with Zirra’s machine learning capabilities.
Here’s a brief description of the the way Nigel assess team, product and momentum:
Team Rating– Team rating is a factor of the LinkedIn recommendations, record evaluation, social sentiment analysis, success and seniority track record, social media feedback, success as previous entrepreneurs, managers, investors, and more.
Product Rating– Product rating is a factor of customer reviews, analysis of product sentiment on the media, current hirings, Google trends analysis of product searches, IP search, usage metrics (downloads, Similar Web), and others.
Momentum Rating– Momentum rating will rate the company’s progress, pace, and acceleration of translating their vision with execution. Momentum will be rated by Alexa and Similar Web trajectories, funding history, frequency, and sentiment of media & news analysis, usage history of the product, and others.
@nigel, what is the valuation of Delivery Hero?
Requesting Nigel “what is the valuation of X” or “Show me the valuation of X,” or “How much is X valued/worth”, will retrieve the estimated valuation of a company.
Nigel’s valuation process is based on Zirra’s proprietary technology, which involves both Intrinsic and Relative valuation algorithms. The intrinsic data includes revenue and expense estimations, traffic trajectories, investment history, IP history, and velocity, based on aggregated sources. In the relative analysis, data is compared and benchmarked with a database of thousands of companies with correlation to stage, space, size, and trajectory.
Estimated valuations and ratings are not shown automatically. They are visible only to paying customers that order research reports on companies. Before being published, a Zirra analyst reviews the information and provides feedback to the model before they they go on to the final report that is delivered to the paying customer.
Risks & Opportunities
@nigel, show me risks and opportunities for Palantir
We saved the best for last. This last piece of technology is definitely a celebration of insights, such that conclude all of the above parameters within one click. Here’ we’ll now be taking all the data and information we’ve been through before and translate it directly to an output that a human analyst would produce in the traditional model of analysis.
By typing any variation of the words “risks”, “challenges”, or “opportunities for” a company, Nigel will pull out the full list of risks and opportunities for a company. Let’s take Lyft for example, by typing “show me the challenges of Lyft”.
Nigel pull out nine points in three different colors: red (risk points), orange (mild risk points) yellow (neutral), and green (success points).
Red: Risk points include an alert of high direct competition with the names of direct competitors within, and an alert of a multitude of legal problems in recent times.
Orange: Mild risk points include an alert of a few layoffs recently, and a statement about the fact that the company has only a few trademarks and no patents at all.
Yellow: Neutral points include an average number of open positions and the statement that traffic that is neither growing nor declining at the moment.
Green: A recent financial round (in the last 6 months, according to Nigel, which corresponds to the $500 million round last April); An extensive media coverage and a large amount of partnerships.
The risks and opportunities module is produced automatically into company research reports sent to Zirra’s paying customers. Nevertheless, we hope to open it to everyone in the near future, adding more new human-generated-type analysis outputs in the near future. This is what we’re most excited about right now.