{"id":26423,"date":"2020-06-26T11:07:25","date_gmt":"2020-06-26T11:07:25","guid":{"rendered":"https:\/\/cityfalcon.com\/blog\/?p=26423"},"modified":"2020-06-26T12:54:51","modified_gmt":"2020-06-26T12:54:51","slug":"new-api-features-for-first-half-2020","status":"publish","type":"post","link":"https:\/\/www.cityfalcon.ai\/blog\/it\/the-startup-journey\/new-api-features-for-first-half-2020\/","title":{"rendered":"Nuove funzionalit\u00e0 API per la prima met\u00e0 del 2020"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">This year has been exciting in terms of new releases, and the CityFALCON product is really taking shape with analytics, more sources, and more services coming online in the first half of 2020. Many of the API services and features are very powerful indeed, and the R&amp;D effort behind them was considerable. For that reason, most of the new features have their own blog posts, so you can more thoroughly understand them. This post is simply to introduce you to what we have achieved so far this year.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">If you would like to see what we\u2019ve done on the consumer side in the first half of 2020, please check out the <a href=\"https:\/\/www.cityfalcon.ai\/blog\/the-startup-journey\/new-web-mobile-features-for-first-half-2020\/\">CityFALCON 2020 Retail Updates post<\/a>.\u00a0<\/span><\/p>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"font-weight: 400;\"><a href=\"#filings\"><span style=\"font-weight: 400;\">Filings from LSE, Companies House, and others<\/span><\/a><\/li>\n<li><a href=\"#nluextraction\">NLU Entity Extraction<\/a><\/li>\n<li><a href=\"#similarstories\">Similar Stories Grouping in 16 languages<\/a><\/li>\n<li style=\"font-weight: 400;\"><a href=\"#sentimentanalysis\"><span style=\"font-weight: 400;\">Sentiment Analysis Scores<\/span><\/a><\/li>\n<li><a href=\"#legalids\">Search by Legal-ID (including private companies)<\/a><\/li>\n<li style=\"font-weight: 400;\"><a href=\"#personalapi\"><span style=\"font-weight: 400;\">Personal API access<\/span><\/a><\/li>\n<li><a href=\"#thefuture\">Concluding remarks and the future<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><a name=\"filings\"><\/a><\/p>\n<h2><strong>Filings from LSE, Companies House, Gazette, and More<\/strong><\/h2>\n<p><span style=\"font-weight: 400;\">Around the beginning of this year, we started serving filings from the London Stock Exchange (LSE) and Companies House in the UK. We have since added The Gazette, and we are about to add filings from the SEC in the United States. We already receive the data and are set up on our staging environment, but we need some more time to push SEC filings to the production environment.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">We published a <\/span><a href=\"https:\/\/cityfalcon.com\/blog\/the-startup-journey\/access-london-stock-exchanges-rns-feeds-on-cityfalcon\/\" target=\"_blank\" rel=\"noopener noreferrer\"><span style=\"font-weight: 400;\">full blog post on our filings release<\/span><\/a><span style=\"font-weight: 400;\">. For now, they are only available through the API, but we will be adding them to the website and mobile apps soon.<\/span><\/p>\n<p><a name=\"nluextraction\"><\/a><\/p>\n<h2><strong>NLU Extraction<\/strong><\/h2>\n<p><span style=\"font-weight: 400;\">Another very valuable feature for enterprises is our NLU extraction service. Again, this one warranted its <\/span><a href=\"https:\/\/cityfalcon.com\/blog\/the-startup-journey\/internal-content-indexing-nlu-service-now-available-on-the-cityfalcon-api\/\" target=\"_blank\" rel=\"noopener noreferrer\"><span style=\"font-weight: 400;\">own blog post<\/span><\/a><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">We have built the service over much of the life of CityFALCON, and we were using it internally to extract entities from text. For example, we algorithmically extract <\/span><i><span style=\"font-weight: 400;\">Amazon<\/span><\/i><span style=\"font-weight: 400;\"> from a headline and mark it as a company for that piece of content.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Combining this with our hierarchical database, the resulting information can be very enlightening. We have Amazon\u2019s ticker, their IRS and SEC numbers, and their associated sector, industry, and subindustry structure.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Now, enterprises can use this service and structured data on their own internal content, such as memos, chats, emails, and internal reports. See the blog post above for a more thorough treatment. We provide NLU entity extraction as a standalone service for indexation of internal content, so subscribing enterprises have no need to purchase other API packages if they do not need them.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Below is an example of the JSON response for a simple message sent between two employees, which provides a lot of insight for companies.<\/span><\/p>\n<span class=\"collapseomatic \" id=\"id6aa35ce82c571\"  tabindex=\"0\" title=\"JSON response for informal message between two employees\"    >JSON response for informal message between two employees<\/span><div id=\"target-id6aa35ce82c571\" class=\"collapseomatic_content \">\n<span style=\"font-family: verdana, geneva, sans-serif;\">{<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;text&#8221;: &#8220;you think the US will launch investigation against Facebook&#8221;,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;lang&#8221;: &#8220;en&#8221;,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;tags&#8221;: [<\/span><\/p>\n<p style=\"padding-left: 40px;\"><span style=\"font-family: verdana, geneva, sans-serif;\">{<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;start&#8221;: 14,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;end&#8221;: 16,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;value&#8221;: &#8220;US&#8221;,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;type&#8221;: &#8220;location&#8221;,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;matched&#8221;: true,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;entities&#8221;: [<\/span><\/p>\n<p style=\"padding-left: 80px;\"><span style=\"font-family: verdana, geneva, sans-serif;\">{<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;name&#8221;: &#8220;United States of America&#8221;,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;type&#8221;: &#8220;geo_regions&#8221;,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;metadata&#8221;: {<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;countries&#8221;: [<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;United States of America&#8221;<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> ],<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;subcontinents&#8221;: [<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;Northern America&#8221;<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> ],<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;continents&#8221;: [<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;North America&#8221;<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> ]<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> }<\/span><\/p>\n<p style=\"padding-left: 40px;\"><span style=\"font-family: verdana, geneva, sans-serif;\">}<\/span><\/p>\n<p><span style=\"font-family: verdana, geneva, sans-serif;\">]<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> },<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> {<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;start&#8221;: 51,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;end&#8221;: 59,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;value&#8221;: &#8220;Facebook&#8221;,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;type&#8221;: &#8220;company&#8221;,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;matched&#8221;: true,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;entities&#8221;: [<\/span><\/p>\n<p style=\"padding-left: 40px;\"><span style=\"font-family: verdana, geneva, sans-serif;\">{<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;name&#8221;: &#8220;Facebook Inc&#8221;,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;type&#8221;: &#8220;stocks&#8221;,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;metadata&#8221;: {<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;legal_ids&#8221;: [<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;0201665019_irs-us&#8221;,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;0001326801_sec-us&#8221;<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> ],<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;tickers&#8221;: [<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;FB_US&#8221;<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> ],<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;categories&#8221;: [<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;Social Media&#8221;<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> ],<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;subindustries&#8221;: [<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;Internet Services &amp; Infrastructure&#8221;<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> ],<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;industries&#8221;: [<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;IT Services&#8221;<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> ],<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;sectors&#8221;: [<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;Technology&#8221;,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;Communications&#8221;<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> ]<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> }<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> }<\/span><\/p>\n<p><span style=\"font-family: verdana, geneva, sans-serif;\">]<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> },<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> {<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;start&#8221;: 22,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;end&#8221;: 42,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;value&#8221;: &#8220;launch investigation&#8221;,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;type&#8221;: &#8220;event&#8221;,<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> &#8220;matched&#8221;: false<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> }<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> ]<\/span><br \/>\n<span style=\"font-family: verdana, geneva, sans-serif;\"> }<\/span><\/p>\n<\/div>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">Tickers and legal numbers gleaned from the NLU service can be fed into the filings service to automate a lot of tasks. One potential internal dashboard that extracts entities then flows into retrieving filings, research, and news content may look like this:<\/span><\/p>\n<div id=\"attachment_26426\" style=\"width: 810px\" class=\"wp-caption alignnone\"><a href=\"https:\/\/blog.cityfalcon.com\/wp-content\/uploads\/2020\/06\/internal-NLU-dashboard-2.png\"><img fetchpriority=\"high\" decoding=\"async\" aria-describedby=\"caption-attachment-26426\" class=\"wp-image-26426 size-full\" src=\"https:\/\/blog.cityfalcon.com\/wp-content\/uploads\/2020\/06\/internal-NLU-dashboard-2.png\" alt=\"\" width=\"800\" height=\"782\" srcset=\"https:\/\/www.cityfalcon.ai\/blog\/wp-content\/uploads\/2020\/06\/internal-NLU-dashboard-2.png 800w, https:\/\/www.cityfalcon.ai\/blog\/wp-content\/uploads\/2020\/06\/internal-NLU-dashboard-2-300x293.png 300w, https:\/\/www.cityfalcon.ai\/blog\/wp-content\/uploads\/2020\/06\/internal-NLU-dashboard-2-768x751.png 768w, https:\/\/www.cityfalcon.ai\/blog\/wp-content\/uploads\/2020\/06\/internal-NLU-dashboard-2-600x587.png 600w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><\/a><p id=\"caption-attachment-26426\" class=\"wp-caption-text\"><span style=\"font-size: 12pt;\"><strong>A potential internal application to assist employees in their research and operations<\/strong><\/span><\/p><\/div>\n<p><a name=\"similarstories\"><\/a><\/p>\n<h2><strong>Similar Stories Grouping in 16 Languages<\/strong><\/h2>\n<p><span style=\"font-weight: 400;\">Similar Stories uses advanced, proprietary machine learning to compare each individual piece of content that we receive for similarity, including news stories, Tweets, and reports. Each piece of content is compared to every other piece using 512 dimensions, such as author and location. Of course, with over 500 dimensions, some may seem like odd combinations and may not mean much to humans, but the correlations Big Data algorithms can draw may uncover some subtle similarities.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">After all the content is compared, groups are formed based on proximity to each other in the similarity comparison vector space. Then, AI chooses the most representative of the group (the <\/span><i><span style=\"font-weight: 400;\">centroid<\/span><\/i><span style=\"font-weight: 400;\">), and this piece of content is marked as the main story, which is returned as the top-level entry in the JSON. Within each top-level JSON entry, the other content in the group falls under the <\/span><i><span style=\"font-weight: 400;\">similar_content<\/span><\/i><span style=\"font-weight: 400;\"> field of that entry.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">On web and mobile, this allows humans to easily skip repetitive content or, conversely, read various takes and angles on the same event.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In the API, this setup can lead to better processing of the various angles. CityFALCON already grouped the content, so your company does not need to research and perform this complicated NLU task. <\/span>You can now focus on making decisions with that similar information instead of tying up resources trying to build the NLU technology &#8211; we developed it for you already. If your application involves serving content to end users, you can remove all of the similar stories and only display the top JSON entries (i.e., unique stories), so they benefit from the same reduction in redundancy.<\/p>\n<p><span style=\"font-weight: 400;\">Moreover, the similarity algorithm works across 16 languages. One use case would be to capture nuance for bilingual teams to analyse and gain insight into the thought process and potential outcomes of events, based on who is writing what when.<\/span><\/p>\n<p><a name=\"sentimentanalysis\"><\/a><\/p>\n<h2><strong>Sentiment Analysis<\/strong><\/h2>\n<p><span style=\"font-weight: 400;\">This is another feature that is so valuable that we wrote an <\/span><a href=\"https:\/\/cityfalcon.com\/blog\/the-startup-journey\/capital-emotions-track-sentiment-for-financial-content-globally\/\" target=\"_blank\" rel=\"noopener noreferrer\"><span style=\"font-weight: 400;\">entire blog post on sentiment analysis<\/span><\/a><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Sentiment Analysis is a powerful analytic that leverages NLU to score content based on how positive, negative, or neutral its language is. Our systems break down content at the clause level, so even a single sentence can have more than one associated sentiment score (one for each clause).\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Furthermore, by using our NLU entity extraction service (internally, of course), we can identify which one of our 300,000 entities in our database is associated with the content in question. Then we build aggregate scores for all of the locations, people, companies, stocks, organisations, and other entity types in the database.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Aggregate groups, such as Sectors (an aggregation of all constituent companies) also get their own scores. The scores for aggregate groups are weighted averages, so while CityFALCON is in the Tech Sector along with Microsoft and IBM, those two generally carry much more weight than CityFALCON because they garner so much more media attention.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">A simplified overview of the system may look like this:<\/span><\/p>\n<div id=\"attachment_26434\" style=\"width: 1072px\" class=\"wp-caption alignnone\"><a href=\"https:\/\/blog.cityfalcon.com\/wp-content\/uploads\/2020\/06\/Sentiment-Analysis-chart-_2x.jpg\"><img decoding=\"async\" aria-describedby=\"caption-attachment-26434\" class=\" wp-image-26434\" src=\"https:\/\/blog.cityfalcon.com\/wp-content\/uploads\/2020\/06\/Sentiment-Analysis-chart-_2x.jpg\" alt=\"\" width=\"1062\" height=\"710\" srcset=\"https:\/\/www.cityfalcon.ai\/blog\/wp-content\/uploads\/2020\/06\/Sentiment-Analysis-chart-_2x.jpg 1408w, https:\/\/www.cityfalcon.ai\/blog\/wp-content\/uploads\/2020\/06\/Sentiment-Analysis-chart-_2x-300x201.jpg 300w, https:\/\/www.cityfalcon.ai\/blog\/wp-content\/uploads\/2020\/06\/Sentiment-Analysis-chart-_2x-768x514.jpg 768w, https:\/\/www.cityfalcon.ai\/blog\/wp-content\/uploads\/2020\/06\/Sentiment-Analysis-chart-_2x-1024x685.jpg 1024w, https:\/\/www.cityfalcon.ai\/blog\/wp-content\/uploads\/2020\/06\/Sentiment-Analysis-chart-_2x-945x632.jpg 945w, https:\/\/www.cityfalcon.ai\/blog\/wp-content\/uploads\/2020\/06\/Sentiment-Analysis-chart-_2x-600x401.jpg 600w\" sizes=\"(max-width: 1062px) 100vw, 1062px\" \/><\/a><p id=\"caption-attachment-26434\" class=\"wp-caption-text\"><strong><span style=\"font-size: 12pt;\">A simplified overview of sentiment analysis connections<\/span><\/strong><\/p><\/div>\n<p><span style=\"font-weight: 400;\">Through the API, this data is served along with entities and content (news stories). A nicely-formatted (pretty-printed) JSON response with sentiment may look like this:<\/span><\/p>\n<p><a href=\"https:\/\/blog.cityfalcon.com\/wp-content\/uploads\/2020\/06\/unnamed-6.png\"><img decoding=\"async\" class=\"alignnone size-full wp-image-26427\" src=\"https:\/\/blog.cityfalcon.com\/wp-content\/uploads\/2020\/06\/unnamed-6.png\" alt=\"\" width=\"777\" height=\"425\" srcset=\"https:\/\/www.cityfalcon.ai\/blog\/wp-content\/uploads\/2020\/06\/unnamed-6.png 777w, https:\/\/www.cityfalcon.ai\/blog\/wp-content\/uploads\/2020\/06\/unnamed-6-300x164.png 300w, https:\/\/www.cityfalcon.ai\/blog\/wp-content\/uploads\/2020\/06\/unnamed-6-768x420.png 768w, https:\/\/www.cityfalcon.ai\/blog\/wp-content\/uploads\/2020\/06\/unnamed-6-600x328.png 600w\" sizes=\"(max-width: 777px) 100vw, 777px\" \/><\/a><\/p>\n<p><a name=\"legalids\"><\/a><\/p>\n<h2><strong>Addition of Legal ID Field for Search<\/strong><\/h2>\n<p><span style=\"font-weight: 400;\">Previously the API only accepted <code>assets<\/code>, <code>tickers<\/code>, and <code>full_tickers<\/code> as input fields to find companies, people, and other targets of requested information. Now, API users can search by <code>legal_id<\/code>, too. This makes integration more standardised and precise. Moreover, it is easier to target private companies that do not have tickers. For example, Revolut in the UK is a very popular company to watch, but it has no standard ticker to identify it. With the <code>legal_id<\/code> field, now API users can target <code>08804411_companieshouse-gb<\/code> to retrieve information on Revolut.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">See the <\/span><a href=\"https:\/\/www.cityfalcon.com\/help\/categories\/360001775273-API-and-Historical-Data-Sets\" target=\"_blank\" rel=\"noopener noreferrer\"><span style=\"font-weight: 400;\">Knowledge Base<\/span><\/a><span style=\"font-weight: 400;\"> for more tutorials and explanations or check out the <\/span><a href=\"https:\/\/dev.cityfalcon.com\/doc\/api\/v0.2\" target=\"_blank\" rel=\"noopener noreferrer\"><span style=\"font-weight: 400;\">documentation <\/span><\/a><span style=\"font-weight: 400;\">to give it a try in the sandbox.<\/span><\/p>\n<p><a name=\"personalapi\"><\/a><\/p>\n<h2><strong>Personal API Access<\/strong><\/h2>\n<p><span style=\"font-weight: 400;\">We have also opened the API for personal use. We saw interest from developers and individuals who wanted to build their own financial and business applications using our data but were unable to purchase full API subscriptions.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Individuals can now use the API to make up to 10,000 calls per month and retrieve story data, the title, description, and the CityFALCON score.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">A personal subscription starts from $20 a month for academia, healthcare, and non-profit users or $40 a month for everyone else. A Premium version is coming soon that offers more features and a higher call limit.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">More details are in the <\/span><a href=\"https:\/\/www.cityfalcon.ai\/blog\/the-startup-journey\/real-time-financial-news-api-for-personal-use-from-20-month\/\" target=\"_blank\" rel=\"noopener noreferrer\"><span style=\"font-weight: 400;\">dedicated blog post on personal API access<\/span><\/a><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><a name=\"thefuture\"><\/a><\/p>\n<h2><strong>Interested Parties and the Second Half<\/strong><\/h2>\n<p><span style=\"font-weight: 400;\">So far this year we have released quite a few major features for the API, and we feel confident in our company\u2019s position to release more in the future. We are proud of what we have accomplished to date and are ecstatic to reap the fruits of years of R&amp;D in data science, infrastructure, and financial data curation.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">We constantly add new content sources, and we are continuing our <\/span><a href=\"https:\/\/cityfalcon.com\/blog\/the-startup-journey\/cityfalcon-wins-six-figure-rd-grant-from-malta-enterprise-will-collaborate-with-university-of-malta\/\" target=\"_blank\" rel=\"noopener noreferrer\"><span style=\"font-weight: 400;\">R&amp;D project in Malta<\/span><\/a><span style=\"font-weight: 400;\"> to expand our language coverage, both from a content standpoint and in machine learning applications. Additional machine learning services for internal data are on the horizon.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">If you are interested in any API services, do <\/span><a href=\"https:\/\/www.cityfalcon.com\/contact-us\" target=\"_blank\" rel=\"noopener noreferrer\"><span style=\"font-weight: 400;\">contact us<\/span><\/a><span style=\"font-weight: 400;\"> for a consultation and demonstration. The better we know your use case and situation, the better product we can provide you.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Quest&#039;anno \u00e8 stato entusiasmante in termini di nuove versioni e il prodotto CityFALCON sta davvero prendendo forma con analisi, pi\u00f9 fonti e pi\u00f9 servizi in arrivo online nella prima met\u00e0 del 2020. 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