Web3 Adoption in Healthcare
Wayne Boulais, Tensility Venture Partners
Armando Pauker, Tensility Venture Partners
Nicholas Shapiro, UPMC Enterprises
Vicky Wang, Kellogg School of Management, Northwestern University
There are categories of healthcare problems that are well-suited for Web3 infrastructure solutions. Existing healthcare institutions are limited by practices and regulations that do not incentivize data sharing across participants. Key issues in healthcare data today include the lack of a full longitudinal data set for a given patient and the struggle by patients to control their own data. With Web3, we can rethink how the participants in the ecosystem can be incentivized and energized to find new ways to share data to improve the healthcare system. Web3 concepts suggest new approaches to addressing the issues of trust, alignment, and transparency.
The Decentralized Autonomous Organization (DAO) is a flexible organizational structure that could be the first way that Web3 ideas begin to impact healthcare. The Web3 smart contract and the blockchain provide the means for incentivizing data sharing in many forms across the healthcare landscape, which consists of patients, physicians, healthcare providers, payers, pharmaceutical companies, and medical research institutions.
The graphic below is a general model of a healthcare DAO. At the highest layer, the founding team determines their mission and strategy. The founding team, in discussion with other participants, determines how data is going to be shared (with some defined opt-in procedure to meet privacy regulations), the incentives for sharing the data, the group governance structure, and how the treasury will be managed. The last layer encompasses the potential constituents of the DAO. Every DAO will have a different set of constituents based on the mission.
Examples of existing and potential healthcare DAOs include:
Of course, there will be distributed healthcare communities that do not use the DAO structure. For example, Hashed Health has started a company, ProCredEx, that “allows members to sell or share verifications they’ve created and purchase verifications they need. ProCredEx’s validation engine and distributed ledger technology securely presents immutable credentials data.” The benefits to the health system are participating in a federated sharing of credentials across all its employees - not just the physicians - to lower the cost for all providers.
Importantly, not all healthcare problems are best addressed by Web3 infrastructure. Careful consideration must be given to matching the appropriate enabling technology with the proposed solution. Deploying Web3 infrastructure for the sake of describing a company as forward-looking will simply add cost and friction to stakeholder adoption. Several examples listed above demonstrate areas where the information sharing that does take place is controlled by centralized clearing houses with significant market capture. Web3 infrastructure, when directed effectively, can erode the control of middlemen that extract meaningful value from stakeholders while providing limited improvement - which leads to a lack of trust and limited sharing. Healthcare innovation using Web3 infrastructure will ultimately succeed in use cases where data creators and owners are empowered and the whole is materially more valuable than the sum of the parts.
*UPMC Enterprises, a division of health system UPMC, owns a financial stake in Hashed Health.
We are excited to announce our investment in Culina Health’s seed round. Based in New York City, Culina Health is a clinical telenutrition platform focused on treating, reversing, and preventing chronic conditions using medical nutrition therapy from registered dietitians (RDs). It provides data-powered personalized nutritional programs, enabled by a patient-facing app, for patients, allows for seamless electronic health record data transfer and feedback for physicians, and provides back-office and administrative help for RDs.
Clinical nutrition centers on the prevention, diagnosis, and management of nutritional changes in patients linked to chronic diseases and conditions. While the wellness nutrition space already sees an abundance of technological solutions such as nutrition apps, clinical nutrition is still highly reliant on an individual RD-based approach with limited technological solutions available and no market leaders, despite the market growth. Clinical nutrition support will provide value for a large population with chronic disease (diabetes, celiac disease, cardiovascular disease, etc.) and other nutrition support needs. There is a huge opportunity in bringing an effective solution to this space.
Culina has developed “The Culina” way of care, where it provides extensive training and education to the RD staff to ensure standardized and quality care. In addition, care delivery data models are developed from data captured from the platform and smartphone, further facilitated by AI-enabled features such as photo interpolation of food to-be-consumed.
We are excited for the founding team to revolutionize the clinical nutrition space. Vanessa Rissetto, RD, co-founder and co-CEO, has 10+ years of experience as an RD and was a dietary director at NYU. She is a highly sought-after dietitian with frequent appearances in the press and media. Steve Kuyan, co-founder and co-CEO, has 10+ years of experience in startup, venture capital, investing, and startup growth. He founded and led NYU Future Labs with 40 exits. Tamar Samuels, RD, co-founder, has 7+ years of experience in hospital and private RD practice. Given the management team’s expertise and recognition in the clinical nutrition space and their experience in start-up operations and growth, Culina Health is uniquely positioned to attract top RD talents and provide quality care to patients.
We believe in the founding team’s vision, and we are excited to partner with them to achieve their mission: democratizing access to clinical nutrition to increase everyone’s healthy life span through personalized data-driven telenutrition!
Web2 to Web3 Convergence in the Enterprise
Wayne Boulais, Managing Director, Tensility Venture Partners
Armando Pauker, Managing Director, Tensility Venture Partners
Alex Poon, Co-Founder, CharmVerse
Distributed Autonomous Organizations (DAOs) became possible with the advent of blockchain and Web3 infrastructure. DAOs are appealing because of decentralization, community building and the promise of shared outcomes. The participants in a DAO can have more input on the direction and governance of the organization than the average employee in a traditional corporation. The flexible structure allows individuals across the globe to seamlessly come together and build a community centered around a common objective. And the token incentive structure allows all the members of the organization to benefit from the collective success of the project.
The first DAO, The DAO, was launched in 2016 on the Ethereum blockchain as an investor-directed investment fund that crowd sourced funds with a token sale. This DAO quickly ran into problems when its smart contract was hacked allowing the hacker to drain 40% of The DAO’s treasury. At the time of the hack, the Ethereum blockchain was only about one year old. In a controversial move, the Ethereum blockchain instituted a hard fork that rolled back the Ethereum history to before the hack. This change allowed the stolen funds to be returned to investors. (See What was the DAO?)
Since 2016 the blockchain ecosystem has gained acceptance and credibility in crypto trading, decentralized finance and non-fungible tokens (NFTs) for collectors and creators. This acceptance has led to renewed interest in DAOs as an organizational model and to fast growth in the number of DAOs. According to DeepDAO.io, in March of 2022, more than 600 new DAOs were formed, and they are now tracking nearly 4,900 DAOs. DAOs are growing at more than 160% annually. Yury Lifshits, the founder of SuperDAO.co, has predicted that one million DAOs will exist in the near term.
The ability to organize and manage people, tasks and money in a decentralized organization is a challenge. Blockchains, smart contracts and tokens are the critical pieces of enabling infrastructure that allow organizations to create and align incentives in a decentralized fashion. Crypto wallets are an essential control point for the DAO to manage role-based access, voting rights and payment methods.
Numerous DAO tooling companies have been created recently to assist in the formation and management of these decentralized organizations (see market map below).
Source: Nichanan Kesonpat, Platform & Content @1kxnetwrk, @nichanank
While there are many different DAOs forming, there are four broad categories of DAOs.
Investment DAOs gather funds to make shared investment decisions in companies, grant distributions or shared collections of art, NFTs and other collectibles. In 2021, the Constitution DAO raised over $42M attempting to buy a copy of the US Constitution. Links DAO is intent on buying a golf course in 2022, while Krause House DAO is a collective effort to buy an NBA team. These DAOs have a strong focus on the protocol they are built upon because a DAO can have large, shared treasuries that require security, transparency and smart contracts to distribute funds into projects, pay contributors and document the approval process.
Social DAOs bring a community together to collaborate around shared interests. They focus on communication methods, community content, and shared values using a token gating process. For example, the Friends with Benefits DAO is a group of artists, thinkers, and Web3 enthusiasts attempting to bridge culture and technology with a creative, Web3-native ethos. The $FWB token enables governance and ownership for the members that share the DAO’s collective values.
Entertainment DAOs enable community driven content decisions for people like film makers, authors, artists and other creatives. These DAOs allow creators to leverage their brand to build a broader ecosystem of content delivered by community members across various channels (podcasts, newsletters, social, etc.).
Product and Services DAOs provide various business offerings. For example, RaidGuild is a design and development agency for the Ethereum ecosystem. Juicebox is a platform for fundraising from the community and building a treasury. DAO Masters and DAO Central are showcasing DAO projects.
Key elements of a DAO:
It is early days for DAOs, but things are moving very rapidly. As DAOs grow and demonstrate success in the Web3 eco-system, we see the potential of their novel organization techniques, tools and processes to be adopted initially where Web 2 to Web 3 businesses converge. Some potential examples are:
Here is a thoughtful blog post by Mitch Worsey, our intern at Tensility Venture Partners, discussing Web3 dynamics and how that may affect Media and Entertainment.
WEB3 PATH TO ENTERPRISE ADOPTION
Wayne Boulais, Co-Founder & Managing Director, Tensility Venture Partners
Armando Pauker, Co-Founder & Managing Director, Tensility Venture Partners
Paul Hsu, Founder and CEO, Decasonic
We, the authors, had the pleasure of connecting our respective areas of investing and operating experiences across enterprise and consumer platforms. Our collaboration takes a fresh perspective at Web3 enterprise adoption. We are energized when sets of expertise come together to innovate a frontier technology.
In this blog post, we are considering what conditions need to be met for Web3 technologies to be ready for enterprise adoption. Web3 encompasses open and decentralized networks, built on blockchain layers, and that employ some form of tokens as a mechanism for collaboration and alignment of incentives. We see this as separate from the current discussions on the metaverse, which encompasses AR/VR components to enhance the end user Internet experiences.
Traditional enterprises will embrace Web3 when they see a path to new revenue growth opportunities: new products, new business models, new customer segments, new geographies, new sales models, and / or new workforce structures. New business models are historically introduced first by disruptive startups and embraced by enterprises later, as the technology matures. Web3-focused hackathons and accelerators today are the places where new ideas are born and incubated. These hackathons, many sponsored by specific blockchains, drive collaboration and creativity with blockchain native organizations. These groups are driven by ad hoc technical teams which create "projects" or applications that can become companies.
The first successful use cases in new technical segments are often focused on end-consumer applications that lead to widespread adoption. This echoes the trajectory of adoption for AI. The first major adoption for AI in the corporate realm was in companies like Facebook, Amazon, Netflix, and Google that collected massive amounts of user data and used that to drive recommendation engines and increase the engagement of each company’s particular content (e.g., ads for Google or movies for Netflix). There are several examples of the early consumer applications of Web3.
1) Bitcoin was consumer-driven for a decade led first by technical early innovators, then retail investors before the leading edge trading firms and hedge funds. Now some e-commerce businesses, some corporate 500 treasuries, and a few governments have moved forward with limited adoption.
2) The NFT (non-fungible token) technology burst on the scene first through the EIP 721 standard in early 2018 and then scaled towards mainstream awareness in 2021: first, video moments with the NBA, then art collectibles, and now sports and celebrity influencers seeking new ways to engage with fans and followers. The blockchain provides clear provenance of ownership, a critical value driver for digital products or services. More recently, AMC and other retail brands began initial engagements - as part of loyalty programs through limited minting.
3) P2E (Play-to-Earn) business models have been introduced for playing online blockchain-based games where NFTs are minted for gameplay and players earn digital coins or tokens. Dramatic experimentation with business models including staking NFTs in games to win more gameplay tokens and the use or sale of NFTs across games is in process now.
4) Staking, verifying transactions, renting, or lending of digital coins for specific periods of time in order to collect fees in the form of more coins is a financial innovation using the peculiar aspects of decentralization and blockchains. Today we see the rise of DeFi (decentralized finance which allows individuals to engage in practices known as yield farming.
5) The DAO (distributed autonomous organization) concept has initial consumer traction in several forms. Bankless DAO started from a podcast (“Bankless”), but has become a sprawling network of new businesses/services created by and for the community. Other examples are the ConstitutionDAO (and its failure to outbid Ken Griffin for the US Constitution) or LinksDAO (with its goal to acquire a golf course exclusive for members).
The infrastructure for these consumer applications is maturing quickly. Crypto exchanges (Coinbase, FTX, Binance) are accessible to the mainstream, simplify the buying and trading for fiat money for digital coin, and enable the purchase and sale of NFTs. Trades are allowed between different digital coins. These exchanges act as central points of liquidity for digital native transactions. Marketplaces like OpenSea have arisen for consumers to efficiently search, find, buy and trade tokens.
For enterprise adoption of Web3, we consider several conditions. There was a previous effort in 2017 to use the blockchain for enterprise applications, but that adoption did not occur. A perspective on why this is different now will be discussed in a subsequent blog post.
1) Scalable infrastructure must be available from the point of view of both cost, availability and speed. The cost of using We 3 resources must approach the cost of cloud hosting today. In Web3 there is already a migration to proof of stake for Ethereum to address the high transaction costs caused by the proof of work approach in Bitcoin and Ethereum 1.0. New alternatives, such as Solana, Polygon, Avalanche, Near and Wax, have been purpose-built to address the cost issue. Other innovations in Proof of Work include Kadena’s chainweb blockchain architecture.
The transaction speed must be capable of communication throughputs similar to current internet and transaction processing speeds. Already new blockchains, like Solana and Avalanche, have been engineered for high transaction speeds. Solana claims to be capable of 50,000 TPS with the combination of proof of stake and proof of history approach. This limit approaches Visa's TPS.
2) Identity/ privacy/ security infrastructure must be accepted, however, the ideas of privacy and identity are being redefined in Web3. The digital wallets used to store digital coins and NFTs have curious properties and implications in this area. These wallets are anonymous, but the contents are visible because the transactions leading to the wallet contents are immortalized in the open public ledger or blockchain. Wallets become the de facto identity in the Web3 world. However, since you can have multiple wallets, you can have and curate multiple identities. This is unique to Web3 and allows for individuals to segment reputations through the contents of their wallets. The wallets can prove, for example, that the holder has NFTs that were only given to attendees of certain technical conferences or to show technical literacy through the earning of badges. These NFTs act as validations of activity or ownership.
3) An understanding of tokens and their power to re-align incentives. Part of the allure of Web3 is the aligned user and growth incentives afforded by the use of tokens. These tokens are the means by which identity or reputation can be established for the purposes of access control, collaboration, or incentive structures. The potential for the increase in value of the tokens also sets the stage for a change in the software licensing model. The transfer of a token as part of a software licensing agreement would allow the buyer of software to have a stake in the success of the software developer and a say in the community of customers that use the software. The more the business model relies on key elements being on the blockchain, then the more likely a token will be a good incentive and governance addition to the business model. Conversely, non-blockchain companies will be very challenged in using tokens because they are not likely to be cost-effective, value-add, or strategic.
4) New possibilities for customer segments or employee organizations. The ability to see inside wallets while keeping identities private brings a new world of possibilities in customer segmentation and data control for the end-user. The ability for the end consumer to control and curate multiple identities may allow for the end consumer to monetize data (through the staking of a specific wallet) that is now gathered, controlled by, and profited by large data economy tech companies. DAOs could allow users to be part of entities where the benefits of unique membership, through special access or unique value, are validated by tokens. We see the potential for DAOs to become enterprise customer advisory groups or select corporate influencers or interest groups approved by HR in distributed organizations once the new governance models become more familiar to businesses.
Like many emerging technology adoption, the Web3 path to the enterprise will be bumpy with many starts and stops. Enterprises will eventually adopt and change after disruptive startups show the way to new customers and revenue, in much the same way that Google and Amazon did in their formative time decades ago. We are excited about this future.
Tackling the Turing Test: Automation Quickly Creates Video Content for Customer Success
Customers of B2B SaaS products depend on videos as their preferred vehicle for customer success information. Many companies maintain vast video libraries that offer a wealth of narrated information in easy-to-follow screen recordings, and customers often prefer this more dynamic format to written instructions. Unfortunately for the enterprises, keeping this library up-to-date is a highly manual process: video recordings take time to produce, are costly to translate into other languages, and – most plaguing of all – can become quickly outdated with subsequent product release cycles. It is not unusual for companies to accumulate ‘video debt’, or a glut of outdated videos that do not accurately represent the latest product version.
We at Tensility understand the importance of Customer Success for B2B SaaS companies, and are excited to announce our investment in Videate’s seed round. Based in Austin, Texas, Videate’s technology uses AI to quickly transform written documentation into finished videos related to support, on-boarding, or training. The manual tasks of recording, adding voiceover, and editing video content are completely automated with an easy-to-use platform that leverages browser automation, NLP, and text-to-speech technology. Videate’s AI eliminates the hassle of software video creation, offering special effect solutions and pronunciation tools to ensure the videos look, feel, and sound like they are human-made. Videate's automated language translations can transform a single piece of content into a globally-relevant resource. With an initial focus on B2B SaaS companies, we are very impressed with the team’s early traction and customer feedback that likens the previously burdensome process to magic.
The management team is made up of a seasoned cohort of leaders and innovators. Co-founders Dave Gullo and Mark Hellinger are former C-suite executives with decades of experience in online video and enterprise application construction. They are highly motivated to tackle challenging problems, and their early traction speaks to their success at addressing a common pain point for SaaS companies, product managers, and B2B customers. We are thrilled by their product roadmap that demonstrates a deep understanding of how to apply AI to delight customers. We look forward to partnering with Videate to transform Customer Success and help B2B companies meet their customers’ needs with ease!
HARNESSING AI IN QUANTUM COMPUTING
We are excited to announce our investment in Agnostiq’s seed round. Based in Toronto, ON, Agnostiq Labs (“Agnostiq”) is developing a suite of applications that seamlessly enable financial institutions (FIs) to leverage QC to power their trading algorithms, all without the need of expensive quantum programming resources. Agnostiq’s applications will allow banks to securely transpile, optimize, and deploy quantum machine learning (QML), quantum Monte Carlo and quantum neural networks in portfolio optimization models. This breakthrough will lead to development of new algorithms at a faster rate and better market predictions.
Financial institutions (FIs) have realized that classical computing is approaching the limit of Moore’s law and there is a gap between the amount of new unstructured data coming in and their ability to process that data to make better decisions. As such, FIs and other organizations are looking to quantum computing (QC) to resolve these issues and deliver the high performance computing they need to maintain their edge. Whether developing the better algorithm to price options or conducting trades in one 64 millionth of a second to capitalize on the arbitrage opportunity, FIs need the compute power to analyze hundreds of millions of data points in real-time to execute their strategies.
While initially focused on banks, we see tremendous opportunity to apply their unique quantum AI workflows and best-in-class security applications across several industries, such as pharmaceuticals, healthcare, and energy. Additionally, we believe Agnostiq can become the platform-of-choice that accelerates enterprise adoption of QC and transforms data scientists into quantum scientists.
We are incredibly impressed with the management team and talent. Collectively, the founders Oktay Goktas, PhD, and Elliott MacGowan possess the unique combination of deep technical knowledge in QC, sales acumen and operational expertise needed to succeed in this nascent industry. Agnostiq has also proven its ability to attract top tier QC talent with backgrounds in quantum physics, cryptology, mathematics, and computational physics. Given the dearth of available and qualified talent, Agnostiq’s ability to attract, hire, and retain top scientists will solidify its market position and competitive moat.
We believe in Oktay, Elliott, and Edwin’s collective vision on quantum computing and are excited to partner with them in their quest to help enterprises harness the power of AI in quantum computing!
Today companies are driving workforce productivity using 3rd party SaaS applications like Salesforce, Jira, Dropbox which form the backbone of critical functions across the organization. According to a 2020 Devsquad study, companies deploy, on average, 34 different SaaS tools, and that number increases dramatically with company size (reference 1 below).
Company tech stacks are also becoming increasingly decentralized and thus harder to manage. Communication tools such as Slack and Microsoft Teams have made it easier than ever to collaborate across teams, but have also led to sensitive information moving unchecked across the enterprise, increasing the risk of data loss and leakage. Last year, over 165 million records were either lost or exposed within the US alone (reference 2 below), all the while increased regulation (e.g., GDPR and the California Consumer Privacy Act) has levied significant fines and put additional pressure on businesses to revamp their information security and data loss prevention (DLP) strategies.
As organizations continue to grapple with this changing landscape, we are thrilled to announce our investment in Polymer Solutions’ (“Polymer”) seed round. Cyber security is one of our key investment areas, and continues to be important as more work moves to the cloud. We are proud to support Polymer’s vision to become the preeminent platform that manages DLP and redaction across the enterprise technology stack. While most of the DLP market has focused on encryption-based solutions for at-rest data, Polymer is unique in its approach by applying Natural Language Processing (NLP) on unstructured, in-motion data to redact Personal Identifiable Information (PII) and sensitive corporate information. This solution will be critical to companies that collect sensitive customer information, such as financial or health data.
Polymer provides an easy-to-use solution that allows enterprise Information Technology departments to create access controls as well as monitor, secure and redact sensitive data across dozens of collaboration apps, including Slack, Github, Dropbox and Zapier. Polymer’s product has already gained significant traction with several large enterprise clients.
Polymer was founded by Yasir Ali and Usman Malik, who are supported by a strong technical team of cyber security, big data and machine learning experts who are excited and well-positioned to tackle this complex data redaction problem. We are thrilled to partner and support Yasir, Usman, and the Polymer team as they continue to expand their data governance platform and grow into a leading security company!
1 ”60 SaaS Statistics and Trends for 2020”, Industry study via Devsquad, 2020
2 “Annual number of data breaches and exposed records in the United States from 2005 to 2019,” Identity Theft Resource Center, 2019
Over $600 billion is spent each year on recruiting activities worldwide, and yet many companies still feel their talent needs are not being met. U.S. companies spend $8,000 - $15,000 and 22-40 hours per new entry level hire, but, because they often target a small pipeline of schools, this investment of time and money does not yield the desired return. Further, companies are looking to increase their return on recruiting investment while addressing shortcomings in diversity and inclusion goals.
Many students and early career applicants want to take advantage of this high demand for their talent, but are unsure how to do so. This lack of clarity is especially acute for students from marginalized or non-traditional backgrounds. They need resources on topics like resume preparation, pitch practice, and networking tips, but don't know where to start and don't identify with generic templates currently on the market.
Upkey has created a solution to empower these students and benefit employers at the same time. Through partnerships with universities, Upkey provides high school seniors and college students with fun, interesting, and engaging learning tracks to help them cultivate a marketable professional image, show off their grit and tenacity, and emphasize their potential. For enterprises, Upkey provides a low-cost tool to reach a wider variety of applicants and remove traditional hiring biases. Each of these solutions are powered by AI engines that provide content recommendations and actionable feedback for both students and recruiters.
We are pleased to announce Tensility has invested in Upkey as a participant in their $2 million seed round led by S3 Ventures. Upkey presents a number of unique advantages over current solutions on the market: First, it creates a data-rich recruiting channel for companies to identify high-quality, diverse talent that may otherwise fall outside traditional recruiting strategies. In addition, these products provide students an alternative to the dry and one-size-fits-all approach to career development. The result is a network of engaged applicants and employers: universities use Upkey to ensure their students are prepared for recruiting while enterprises use Upkey to expand their recruiting footprint cost-effectively.
Upkey was established in Chicago, Illinois in 2014 by Amir Badr, who was previously the diversity lead at Excelon. He was inspired to start Upkey as a way of solving some of the pain he felt as an immigrant in the United States. Upkey has a vision to build an inclusive talent development service that helps students of all backgrounds become more confident and capable of achieving professional success, and we are excited to contribute to that mission.
Today, businesses are generating a massive amount of data every second across hundreds of disparate data sources. As organizations attempt to capitalize on new ML/AI capabilities, each new system or tool disaggregates the journey from data to business value even further, creating costly, slow, and labor-intensive data preparation. The situation creates challenges for the data engineering teams to keep up with business and technical demands.
In machine learning, a "feature" is an input variable, similar to the explanatory ("x") variable in simple linear regression. A machine learning project might use hundreds or even millions of features, and each feature must be paired with labels (similar to the dependent "y" variable) to train a model. A robust and scalable ML/AI development program requires improving the feature extraction process, an early step in ML that prepares data for analysis by abstracting complex schemas and their data into basic objects and attributes.
Relying on reference architectures for feature re-use can help, but this introduces issues of latency, complexity, and another data silo to be managed. To simplify and speed up feature extraction and re-use, a new technology has arisen, called feature stores, which assists with the demanding data preparation required for effective ML. No longer unique to the capabilities of large firms like Uber and Airbnb, feature stores can transform raw data into feature values, store those features, and serve those features for training and analysis in the future.
Importantly, feature stores do not remove the need for Snowflake or similar cloud solutions. Feature stores easily overlay with existing data infrastructures, enabling almost instantaneous updates, reducing risk, and scaling quickly with an enterprise. The graphic below compares feature stores to current approaches.
In short, all of an organization’s data can be converted to reusable features and analyzed with full fidelity, regardless of format or source location, for immediate analytics. Not only does this speed up a data scientist's development timeline, but it brings economies of scale to ML organizations by enabling collaboration. When a feature is registered in a feature store, it becomes available for immediate reuse by other models across the organization.
One example of a leading provider of feature store capabilities is Molecula, who recently completed a $17.6 million Series A round with Tensility as a participant. Molecula leaves data at its source and continuously extracts and updates only features into a centralized feature store. This process eliminates the need to copy, move, or pre-aggregate data, reduces the data footprint by 60-90 percent, and provides a secure data format for sharing.
Whether through Molecula or another organization, feature stores pair with current systems to enable prescriptive analytics while reducing complexity, costs, and risk. We are excited at the capability they provide to data engineers and data scientists to improve the data pipeline and leverage all of a company's data for better business outcomes.
Armando and Wayne