Startup Expert Network Technology Provider Licenses Platform to Macquarie

Macquarie Capital made a minority investment in expertise matching platform provider DeepBench and will be utilizing the firm’s capabilities to facilitate high-touch access to Macquarie’s research analysts and other staff.  DeepBench has shifted its primary business model from being an expert network to supplying expert network technology to financial institutions, consulting firms, and other enterprises seeking to showcase their expertise.

Macquarie’s research department was the original adopter of DeepBench’s platform to package analyst access as a distinct service post-MiFID II.  Macquarie’s implementation is not limited to analysts, however, featuring access to salespeople, traders, bankers and other professionals.  Macquarie was one of the first banks to adopt explicit pricing for its research in the run-up to MiFID II, concurrent with the early 2017 launch of Macquarie Dimension, a solution that offered interactions data and used machine learning to suggest relevant research based on subscriber usage patterns.

Other customers of DeepBench’s enterprise expertise matching platform include Philadelphia-based consulting firm Concinnity and Middle East consultancy MENA Council. DeepBench also plans to launch platforms for a large US-based university and a Fortune-100 tech company in the coming months.

Besides a minority investment from Macquarie, DeepBench is funded by angel investors, including Will Thorndike, managing general partner of private equity firm Housatonic Partners and Ross Mason, founder of MuleSoft which was acquired by Salesforce for $6.5 billion.

The firm was founded in 2017 by four MIT students, led by Yishi Zuo who had previously used expert networks when he was an associate at San Francisco hedge fund Solstein Capital.  The initial concept was to create an expert network modeled as a marketplace rather than as a concierge service. In 2018, the company developed a business line to license expertise matching & management technology to firms seeking to monetize their internal talent.  “Our ambition is to be the Google of enterprise expertise,” said Yishi Zuo in an interview.  “Our long-term vision is to become the default platform that all employees and customers will go to when they need a question answered by an expert, and DeepBench will provide a comprehensive graph of expert knowledge for every enterprise.”    The Boston-based firm currently has 8 full-time staff.

Despite its innovative approach to MiFID II’s research unbundling regulations, Macquarie has not been immune from MiFID II’s ill effects.  The firm exited its Canadian cash equities business in May 2019 after downsizing its London research staff in 2018, prompting the departure of its head of European research Shai Hill.

Our Take

Although technology is a key component of DeepBench’s business plan, it has chosen a different approach than AI-centric startups such as New York-based NewtonX, London-based proSapient, or techspert.io, which originated from Cambridge University.  Rather than competing directly with established expert networks like industry leader Gerson Lehrman Group or its fast-growing rival AlphaSights, DeepBench is pursuing a differentiated strategy of facilitating the expert network-type ambitions of firms with high internal expertise.

For many years, investment banks have sourced third-party experts through their corporate access teams, but it is only with the advent of MiFID II that they have begun to systematically monetize high touch access to analysts and other internal experts.  DeepBench was not the only expert network to see MiFID II as an opportunity.  In November 2018 Coleman Research launched a platform designed to help sell-side firms and boutiques market analyst availability, schedule interactions, manage subscriptions, and invoice clients for analyst access and meetings.  Ironically it is startup DeepBench which was the first to land an investment bank seeking to leverage expert network technology as a source of incremental income.