Golden raises $14.5m Series A led by a16z, closes $1m US Air Force contract, and Marc Andreessen joins board

Since we formally launched in 2019, our team has been hard at work executing our vision to build an extensive database and graph of knowledge for humanity, including practical commercial tools and community features to aid discovery and decisions. Today, we have some great news! I’m very proud to announce that we have raised a $14.5m Series A, bringing our total funding to just under $20m, led by a16z with Marc Andreessen joining the board.

Participating investors include DCVC, Gigafund, Harpoon Ventures, Chris Lyons & the a16z Cultural Leadership Fund, WndrCo, Great Oaks Venture Capital, Vela Partners, HNVR, Socii Capital, Howie Liu (CEO of Airtable), Alex Tew (CEO of, Brianne Kimmel of Work Life Ventures, Augusto "Aghi" Marietti (CEO of Kong), Balaji Srinivasan (ex CTO of Coinbase), Jonathan Swanson (founder of Thumbtack), Jacob Gibson from Better Tomorrow Ventures, Charlie Delingpole (CEO of ComplyAdvantage), Daniel Ha (Founder of Disqus), Tikhon Bernstam (Co-founder of Scribd & Parse), Neal Dempsey of Bay Partners, Ryan Pawell (CEO of Indee Labs) and other great investors.

These investors join prior investors in Golden’s seed round including a16z (who co-led the seed round), Gigafund, Founders Fund, SV Angel, Joe Montana on behalf of Liquid 2 Ventures, Aston Motes (1st employee at Dropbox), Christina Brodbeck (1st designer of YouTube), Lee Linden, Immad Akhund (my cofounder at Heyzap, now CEO of Mercury), Josh Buckley, James Smith (CEO of Bugsnag), James Tamplin (Founder of Firebase), Jack Smith, Mike Einziger of Incubus, Sumon Sadhu, Paul McKellar (Square founding team), Trip Adler (CEO of Scribd) and many other great angels.

In addition to the raise, we’d like to announce we have closed a $1m contract with the U.S. Air Force to help fight COVID-19 with information and knowledge derived from fragmented public sources.

We will be using our Series A funding to further build out the team, product capabilities and datasets.

Build, build, build

Since we launched our first commercial offering, we have gone on to execute the first phase of our roadmap, build out client requested features and take risks with some new experiments:

Compiling topics of interest using Golden Knowledge Graph powered Lists: Based on client feedback we have added the ability to construct custom lists of entities and topics. By setting up specific canonical columns, you can create a live view of data which self updates -- as the Golden Knowledge Graph keeps changing, your own data view also changes. No more dead spreadsheets 🙂

Managing your organizations' knowledge using private fields on canonical entities: In addition to canonical fields, we have added the ability for you to add private fields to a canonical entity or topic. This is stored in your own private organization’s view and accessible to your team only. There is great advantage to not having to maintain fields that have canonical answers, getting the privacy for your own custom fields and having the comparative value of canonical fields alongside private fields. We are excited to see where this goes in terms of opening the door to storing organizations’ knowledge without reinventing the wheel when it comes to knowledge on entities but still allowing the privacy organizations require.

Making querying easier with query templates: We have upgraded our Golden Query Tool in many ways -- from look and feel to more functional elements. This includes the ability to request data on a particular attribute of an entity or entire column for a given query, editing the Golden Knowledge Graph directly from the query tool, and using query templates to short cut constructing queries.

Research with higher precision with the extension of the Research Request engine: On Golden we have attempted to productize research that has previously occurred manually via long winded web searches by building various flows that capture requests at different levels of abstraction.

Paying users can request rich, deep information about an entity or topic or a specific query e.g. ‘who are all the PPE manufacturers within 60 miles of Texas’ or a compilation of information around a group of topics (what we call a cluster). We have now extended this to request a specific attribute of a topic e.g. ‘what is the location of this company’ or ‘weight of this product’ or ‘date this particular legislation was released’.

When we get this request we execute it within a certain time frame and get it back over to the client for feedback. Over time this increasingly builds out the public Golden Knowledge Base. Win-win! In a sense, we have effectively ‘SLAed’ research into canonical information.

Getting to richer data by extending our canonical fields: We have improved our entity model by including new fields: for example, ‘competition’, ‘app store links’ 'D-U-N-S number' and many others. We have been listening to customers and users requests to capture fields that we didn’t have and continue to keep adding new fields to get comprehensive structured data on a topic or entity.

Expansion of the API: In addition to the enrichment and discovery use cases of the API, we have brought the research request model to our API. So not only can you request canonical data on a topic via our site, you can do so programmatically with our API and receive the data back via web-hooks.

Maintaining context with Topic Quick View: In certain views of Golden data, specifically in the Golden Query Tool and Lists, users can now see a quick preview of a topic without having to leave that particular view. This can be useful for quickly reviewing many topics and entities.

Navigating similarly named entities with disambiguation mode: When editing Golden, searching for topics and entities can run into disambiguation issues, it’s now possible to view all the topics and entities which could be relevant making it easier to select the correct entity. This matters at the scale of entity count we are operating at.

New user docs: We’ve recently rewritten, restructured and expanded our user documentation to cover all the new features in Golden, and to make documentation of existing features clearer and more helpful.

Always more data: We have built out many new data sets and data pipelines to feed data into Golden at a faster rate. We’ve added millions of entities into our database, and many more facts. We’ve expanded clusters into areas such as COVID-19, RNA therapeutics, Brain-Computer Interfaces, opened new queries into COVID-19 vaccines, testing companies, unicorns, the latest YCS20 batch  advanced materials companies, nuclear power companies and many more. We expanded our entity types to include things like strategic partnerships, clinical trials, products, legislation and more.

I can’t wait to see how the Golden platform will evolve in our next phase and am really excited to take the product to the next level with our team, customers and community.  If you are interested in being a customer please contact us by requesting a demo here or emailing us directly.

Scaling our team

We are looking for hires across multiple positions including NLP specialists, data engineers, data scientists, a head of data engineering, crawler specialists, ML infrastructure specialists, an internal recruiter, initial sales people in both commercial and government arenas, engineering leadership and lead marketing positions. If you are interested (or see a role we didn’t mention but would be critical to our mission) please get in touch.

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