Adaptive Management launched a new capability for its DataMonster platform designed to source and trial new data vendors. The new service will likely accelerate the number of vendors available through the DataMonster platform.
The new Discover 0ffering
Datamonster Discover provides information about the data offered by over 100 vendors, detailing frequency, history, pricing along with descriptions of the datasets offered. The platform allows searches by ticker to find relevant data sets, with plans to expand search capabilities to include sectors, industries, themes and other factors.
Users can directly contact the vendor to request permission to trial the data. For vendors already integrated on the platform, trials can start the same day with vendor approval. The Discover service also profiles vendors not yet integrated onto the platform, but willing to do so if there is user demand.
An important component of the Discover offering is a data sourcing team comprised of data analysts and former PMs/analysts who can recommend potential data vendors not yet profiled in the Discover product as well as data techniques.
DataMonster Discover is sold as a separate package which includes a set of sourcing projects where Adaptive Management works with a client’s investment team to recommend data sources that can answer their thesis questions around portfolio names. Discover can be bundled with DataMonster’s other capabilities or sold as a stand-alone offering.
The core DataMonster platform
DataMonster is sold as a turnkey alternative data platform which facilitates the onboarding of new datasets. Its primary focus is to visually combine and compare data across vendors and datasets. It also offers an API for advanced users with an Excel Plugin slated for release later in the year.
The platform allows users to integrate existing alternative data with any new datasets being evaluated. When in the testing phase, clients can leverage Adapative Management’s enterprise license with Factset to incorporate FactSet data into the evaluation. During trials or once data is acquired, users do not need to download files or connect to APIs to access data. All data is mapped to a common ticker taxonomy.
Clients are primarily hedge funds but include sovereign wealth funds and private equity firms. Adaptive Management’s business model is partly a seat-based subscription model in which clients purchase access for specific users within their organization. Subscription costs of the datasets used on the platform are separate. Alternatively it operates under a service-based model for its data sourcing and R&D service, as well as DSaaS (data science as a service) for bespoke projects.
Unlike alternative data marketplaces, Adaptive doesn’t charge sales commissions to vendors when it generates new business. The analytic tools available on the platform are also attractive to smaller data vendors which haven’t built their own visualization capabilities. The platform handles entitlements and its modeling capabilities can be used by vendors to build use cases.
Adaptive Management background
Adaptive Management was co-founded in 2014 by Brad Schneider, an MIT-trained computer engineer who was a portfolio manager at Tiger Management, along with co-founder Kevin Thompson, a former security researcher at the National Security Agency. After graduating from MIT, Schneider had co-founded a small data analytics company that worked with Fortune 500 companies to help them mine customer insights from transaction data. After becoming a portfolio manager in hedge fund industry following the technology sector, he began using different datasets to support his portfolio decisions, which was the initial impetus for DataMonster.
Based in New York’s Silicon Alley, Adaptive Management has 30 employees and its website currently lists 11 open positions. The firm completed a seed round in 2016 and is currently raising a Series A funding round.
Rather than building an alternative data marketplace, Adaptive Management is positioning itself as a data sourcing sandbox. This represents a slight shift from its original positioning as a turnkey alternative data platform as the firm de-emphasizes its data modeling capabilities.
In some ways DataMonster Discover is analogous to BattleFin’s Ensemble platform which is also intended to find, test and evaluate alternative data sources. However, DataMonster already has a large population of existing datasets, while the Discover capability is designed to attract more as its data sourcing team recommends new datasets to existing clients.
The new emphasis on data sourcing also competes with Yipitdata’s promotional website, alternativedata.org, which lacks the depth of information offered by DataMonster Discover but is freely available. More direct competitors are London-based data scouting firm Neudata and Dublin-based Eagle Alpha, which upgraded its database of data vendors earlier this year. However, neither of the data sourcing competitors offer sandbox capabilities and, unlike Eagle Alpha, Adaptive Management does not charge sales commissions to vendors for recommending them, relying solely on fees from its buy-side clients.