Over the past 20 years, the venture capital industry has gone through the same explosive growth as the technology companies it has funded. In truth, however, very little of the extraordinary tech innovation and disruption that has taken place during this period has trickled down to venture capitalists like us. Our day-to-day work experience is a surprisingly low-tech affair. In fact, in terms of the actual stuff we do, not the stuff we talk about, being a VC professional is a practically artisanal experience compared to, say, that of being a marketer, a baseball scout, a web developer, or a humanities professor.
We admit that some notable changes have taken place on the edge. For instance, back office, reporting, and pipeline functions are (slowly) moving from spreadsheets to purpose-built cloud solutions. Off-the-shelf data cubes and other increasingly powerful analytical tools are augmenting our ability to assess later stage, data rich companies. And, of course, we are accessing the same video conferencing tools, collaboration platforms, travel apps, and news feeds that are available to anyone with a data connection.
Still, the fundamental work of a VC professional has changed very little over the last 20 years and hardly at all over the last 10 years. Here we are in 2009 trying to flesh out the market opportunity for an enterprise software company:
First stop Google. Hit a wall. Talk to friends and peers. Go through old emails and documents. Speak to customers (if possible). Try to get equity research. Talk to existing portfolio companies. More Google. Plod through SEC filings. Ask the company. Dismiss their work as biased. Google again. Call other friends to see if they have done this work. Talk to consultants (if desperate). Go back to company. Mix. Iterate. Witchcraft. Manually input data from research into Excel. Refine Excel and add charts. Circle back to Google for finishing flourishes of wisdom. Complete document.
Here we are in 2019 trying to accomplish the same thing:
Cut and paste the 2009 workflow.
This process is as labor intensive in 2019 as it was in 2009. Furthermore, we are as uncertain in 2019 about the exhaustiveness of our research as we were in 2009.
What’s true for us is true for most participants in the business of knowledge work, a term first coined by Peter Drucker in The Landmarks of Tomorrow. In addition to venture capitalists, this includes research analysts, consultants, bankers, asset managers, competitive intelligence specialists, investor relations officers, lawyers, business development experts, corporate strategy professionals, and many others. All are suffering the same fate.
This is astonishing considering the remarkable progress in AI over this period, particularly with the widespread implementation of artificial neural networks. Obviously, Google has improved over the last 10 years and collaboration has become easier. At the same time, the amount of information and the attendant noise has increased by an order of magnitude. Cutting through the noise is painstaking and imperfect. In many respects, the democratization of information has made things worse. If only there were a Google for business.
Enter AlphaSense. Over 10 years ago, Jack Kokko (CEO / founder) and Raj Neervannan (CTO / co-founder), two prisoners of the same knowledge work dilemma, met while studying for a Wharton MBA and embarked on a mission to change this dynamic by augmenting our workflow with best-in-class AI.
Today, AlphaSense provides a true AI-based search engine for market intelligence. It enables knowledge workers like us to search, navigate, annotate, and analyze key data points, trends, and themes from thousands of previously fragmented data sources, including corporate filings, transcripts, news sites, broker research, and regulatory documents as well as internal content such as presentations, emails, notes, and other unstructured information.
The company’s platform leverages millions of industry-specific proprietary datasets and uses a blend of natural language processing and machine learning algorithms to identify entities, relationships, and context, enabling it to provide highly relevant results in a structured, scored format. AlphaSense has also built additional layers of functionality that provide best-in-class sentiment and thematic extraction and workflow capabilities.
Here are some examples that showcase AlphaSense’s current capabilities:
- Find exhaustive results for business themes such as “stock repurchases,” where equivalent concepts such as “equity buyback” and “authorized buyback” need to be surfaced, while at the same time, false positive concepts such as “debt repurchases” need to be excluded.
- Differentiate between entities (e.g., Slack, the company) and words (e.g., slack in the economy) in unstructured data.
- Surface precise data when searching for concepts with very high noise-to-signal ratio (e.g., searching for “cystic fibrosis R&D” to find the amount being spent on research in cystic fibrosis, while excluding other irrelevant information.
- Discover themes adjacent to target terms (e.g., discover trends in battery technology when searching for trends in electric vehicles).
- Identify and reproduce for export semi-structured data such as financial statements, lists, and tables.
- Leverage the collective intellect of your peers by sharing knowledge and notes across your team and making internal content discoverable within the platform.
In a nutshell, with AlphaSense we can go much wider, deeper, and faster in the pursuit of intelligence. And the more we use it, the better it becomes. In the age of information overload, data driven decisions based on exhaustive, highly efficient research become attainable. For knowledge work, this is a profound change from the past and represents the true promise of AI.
Unsurprisingly, AlphaSense has grown rapidly and is currently used by over 1,000 enterprise customers, including more than 50% of the S&P 100 corporations and over 66% of the 50 largest global investment firms. The company is also delivering benchmark-beating metrics in customer acquisition, satisfaction, and retention.
Because the two of us focus predominantly on enterprise solutions, it’s rare that we have an opportunity to invest in great companies whose products we genuinely use at work. We are therefore thrilled that AlphaSense selected Innovation Endeavors, after becoming passionate users, to lead its $50 million Series B round. In a somewhat beautiful circular fashion that hasn’t escaped us, the company will use the proceeds from our investment to improve a product we already love.
With this investment, we are commencing our most recent fund’s expansion-stage investment strategy, where we seek to invest in companies with proven commercial traction, huge market opportunities, exceptional products, and world class management teams.