FiscalNote is a the quick, customized way for you to receive government information online.
Jiajun – top recommender systems from GrouponAndrew – wrote much of the initial NLP models (Brown Corpus) and 30+ years of NLP experience
Talk about experience heading up the NYA in Washington, DC = Information is currencyGovernment Information (Unstructured data: Legislation, Regulations, even Speeches) move markets and affect business decisions.Newspapers and Lawyers are realizing that their methods are too costly and slow. Information has fragmented. And no easy way exists to get relevant state and local government information quickly and reliably. * Patton Boggs (largest government regulations lobbying firm just laid of 17 partners) * State and Local Reporting is down 80% in the last 2 decades with massive layoffs in the Journalist industry (while National news is up)* According to the National Federation of Independent Businesses, the #1 concern for small and medium size businesses is keeping up with new laws and regulations (high uncertainty)
Make it easier to understand government impact
We’re not just replacing these institutions, we’re on the cutting edge of the future of newsESPN and Bloomberg already following this model with their instantaneous articles based on sports scores or stock news. Do for politics what was done for finance and sports.
Followthemoney.orgState of the Media (Pew)
Scraper that takes information on pending legislation across all 50 states every 200 microsecondsNews and tweet analyzer that tracks current micro trendsMapReduce function to get relevant bills for an industry and portions to applySentiment analysis and relational algorithm (moneyball for politics) to predict legislation
This new product is marketed to those most impacted by government actions, including influencers (NGOs, associations, etc.), and business leaders (C-suite executives, federal contractors, internal government affairs teams, etc.). The product brings the an unparalleled level of data-based and fact-based, objective reporting and analysis to policymaking.
1 Million in ARR 2013 4.56 Million in ARR 2014 10,000 for hedge funds and financial firms like Goldman, 8,000 for companies like Pfizer (foreign companies, fortune 500, federal and state agencies, etc.) and <300 for local government agencies/non-profits/charities. Current monthly burn: 12,000/mo ramping up to 185k Expected net income by end of year (740k)Contract Size: $2,500/moProj. Lifetime Value: $150,000Engagement: 10-15 EmployeesCost Savings: $162,000/yr+CAC: $5,200 Exclusive licensing if client is willing to pay for 20% of Market
Machine learning algorithms become better with more data
Our vision world domination
Series A next Spring (10 month runway)Very hands on (demos)
Transcript of "FN"
Real-Time Government Analysis
Timothy Hwang | Jonathan Chen | Gerald Yao
Jonathan Chen, CTO
University of Maryland,
Gerald Yao, CFO
Tim Hwang, CEO
Lead Back End
Lead Front End
Senior Back End
Team and Advisors
YS Chi, Advisor
* Chairman, Elsevier (Global FN 500)
* President, International Publishers
Chris Lu, Advisor
* Senior Advisor to President Obama
* White House Cabinet Secretary
* Executive Director, Obama Transition Team
Andrew Mackie, PhD
Information has fragmented
Government Information moves markets and affect
Newspapers and Lawyers are realizing that their methods
are too costly and slow.
Information has fragmented. And no easy way exists to
get relevant the information quickly and reliably.
A web platform that aggregates, analyzes, and predicts
government information using machine learning and NLP.
The Future of News 5
1850 1960 20102000
Local Newspapers Television Social Media Machine Learning
PoliticalGenome Project 6
algorithms and allows for
Allows for comparison of
Brings in the actual
electoral element of
Building a political graph over the entire world.
Market Size 7
Total Spending on Policy Analysis
Total Spending on Newspaper Subscriptions
Track Legislation and News Get Relevant Portions Predict
Market Adoption 9
West Coast Government
National Conference of
Industries most affected
by local/state law (real
Financial firms (hedge
funds, investment banks)
groups refer to local
Contractors refer to local
and state agencies
Early Adopters Early Majority Late Majority
Est. Oct. 2013
MVP II w/ Mobile
Est. Dec. 2013
We move fast.
Est. Jan. 2014
We charge a monthly subscription for each organization.
AVG MO. FEE
Competitive Advantages 13
Proprietary ScraperProprietary Algorithms
We are currently the only
company to apply machine
learning to political
Prediction and optimized
Current algorithm scrapes
legislation across all 50
states in less than 200 ms
(building top 10 cities in US)
Proprietary NLP Models
Competitive Industry Intuitive Design and Use
First and only company to
create legislative and
government taxonomy of
linguistic NLP models.
Nothing technical or “mathy”
– very easy to use for public
“Keeping Up with the Jones’”
Our Vision 14
1. Expand Government
3. Open Data Platform2. Global Expansion
cases, speeches, and
Union, South America
(all confirmed with
Letters of Intent)
Third party algorithms
(IBM, Accenture, etc)
and data visualization
1. More Developers for NLP
2. Business Development to close 100
3. Move Office to DC
4. Test Assumptions
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