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This crypto monitoring startup — ‘We’re bomb-sniffing dogs’ — just raised Series A funding
Solidus Labs, a company that says its surveillance and risk-monitoring software can detect manipulation across cryptocurrency trading platforms, is today announcing $20 million in Series A funding. It’s pretty great timing, given the various signals coming from the U.S. government just last week that it’s intent on improving its crypto monitoring efforts — such as the U.S. Treasury’s call for stricter cryptocurrency compliance with the IRS.
Of course, Solidus didn’t spring into existence last week. Rather, Solidus was founded in 2017 by several former Goldman Sachs employees who worked on the firm’s electronic trading desk for equities. At the time, Bitcoin was only becoming buzzier, but while the engineers anticipated different use cases for the cryptocurrency, they also recognized that a lack of compliance tools would be a barrier to its adoption by bigger financial institutions, so they left to build some.
Fast forward and Solidus today employs 30 people, has raised $23.75 million, and is in the process of doubling its head count to address growing demand. On Friday, we talked with Solidus’s New York-based co-founder and CEO Asaf Meir — one of those former Goldman engineers — about the company’s new round, which was led by Equity Partners, with participation from Hanaco Ventures, Avon Ventures, 645 Ventures, the cryptocurrencies derivative exchange FTX, and a sprinkling of government officials, including former CFTC chair Chris Giancarlo and former SEC commissioner Troy Paredes. We also talked about the kinds of crypto crimes that are on the rise. Excerpts from that chat follow, edited lightly for length.
TC: Who are your customers?
AM: We work with exchanges, broker dealers, OTC desks, liquidity providers and regulators — anyone who is exposed to the risk of buying and selling cryptocurrencies, crypto assets or digital assets, whatever you want to call them.
TC: What are you promising to uncover for them?
AM: What we detect, largely speaking, is volume and price manipulation, and that has to do with wash trading, spoofing, layering, pump and dumps and an additional growing library of crypto-native alerts that truly only exist in our unique market.
We had a 400% increase in inbound demand over 2020 driven largely by two factors, I think. One is regulatory scrutiny. Globally, regulators have gone off to market participants, letting them know that they have to ask for permission, not forgiveness. The second reason — which I like better — is the drastic institutional increase in appetite toward exposure for this asset class. Every institution, the first question they ask any executing platform is: ‘What are your risk mitigation tools? How do you make sure there is market integrity?’
TC: We talked a couple of months ago, and you mentioned having a growing pipeline of customers, like the trading platform Bittrex in Seattle. Is demand coming primarily from the U.S.?
AM: We have demand in Asia and in Europe, as well, so we will be opening offices there, too.
TC: Is your former employer Goldman a customer?
AM: I can’t comment on that, but I would say there isn’t a bank right now that isn’t thinking about how they’re going to get exposure to crypto assets, and in order to do that in a safe, compliant and robust way, they have to employ crypto-specific solutions.
Right now, there’s the new frontier — the clients we’re currently working with, which are these crypto-pure exchanges, broker dealers, liquidity providers and even traditional financial institutions that are coming into crypto and opening a crypto operation or a crypto desk. Then there’s the new new frontier; your NFTs, stablecoins, indexes, lending platforms, decentralized protocols and God knows what [else] all of a sudden reaching out to us, telling us they want to do the right thing, to ensure the users on their platform are well-protected, and that trading activities are audited, and [to enlist us] to prevent any manipulation.
TC: How does your subscription service work and who is building the tech?
AM: We consume private data from our clients — all their training data — and we then put it in our detection models, which we ultimately surface through insights and alerts on our dashboard, which they have access to.
As for who is building it, we have a lot of fintech engineers who are coming from Goldman and Morgan Stanley and Citi and bringing that traditional knowledge of large trading systems at scale; we also have incredible data scientists out of Israel whose expertise is in anomaly detection, which they are applying to financial crime, working with us.
TC: What do these crimes look like?
AM: When we started out, there was much more wholesale manipulation happening whether through wash trading or pump and dumps — things that are more easy to perform. What we’re seeing today are extremely sophisticated manipulation schemes where bad actors are able to exploit different executing platforms. We’re quite literally surfacing new alerts that if you were to use a legacy, rule-based system you wouldn’t be able to [surface] because you’re not really sure what you’re looking for. We oftentimes have an alert that we haven’t named yet; we just know that this type of behavior is considered manipulative in nature and that our client should be looking into it.
TC: Can you elaborate a bit more about these new anomalies?
AM: I’m conflicted about how much can we share of our clients’ private data. But one thing we’re seeing is [a surge in] account extraction attacks, which is when through different ways, bad actors are able to gain access to an account’s funds and are able in a sophisticated way to trade out of the exchange or broker dealer or custodian. That’s happening in different social engineering-related ways, but we’re able, through account deviation and account profiling, to alert the exchange or broker dealer or financial institution we’re working with to avoid that.
We’re about detection and prevention, not about tracing [what went wrong and where] after the fact. And we can do that regardless of knowing even personal identifiable information about that account. It’s not about the name or the IP address; it’s all about the attributes of trading. In fact, if we have an exchange in Hong Kong that’s experiencing a pump and dump on a certain coin pair, we can preemptively warn the rest of our client base so they can take steps to prepare and protect themselves.
TC: On the prevention front, could you also stop that activity on the Hong Kong exchange? Are you empowered by your clients to step in if you detect something anomalous?
AM: We’re bomb-sniffing dogs, so we’re not coming to disable the bot. We know how to take the data and point out manipulation, but it’s then up to the financial institution to handle the case.
Pictured above: Seated left to right is CTO Praveen Kumar and CEO Asaf Meir. Standing is COO Chen Arad.
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BluBracket nabs $12M Series A to expand source code security platform
BluBracket, an early-stage startup that focuses on keeping source code repositories secure, even in distributed environments, announced a $12 million Series A today.
Evolution Equity Partners led the round, with help from existing investors Unusual Ventures, Point72 Ventures, SignalFire and Firebolt Ventures. When combined with the $6.5 million seed round we reported on last year, the company has raised $19.5 million so far.
As you might imagine, being able to secure code in distributed environments came in quite handy when much of the technology world moved to work from home last year. BluBracket co-founder and COO Ajay Arora says that the pandemic forced many organizations to look carefully at how they secured their code base.
“So the anxiety organizations had about making sure their source code was secure and that it wasn’t leaking, from that standpoint that was a big tailwind for us. [With companies moving to a] completely remote development workforce, and with code being so important to their business as intellectual property, they needed to get that visibility into what vulnerabilities were there,” Arora explained.
Even prior to the pandemic, the company was finding they were gaining traction with developers and security pros by using a bottom up approach offering a free community version of the software. Having that free version as a top of the funnel for their sales motion was also helpful once COVID hit full force.
Today, Arora says the company has multiple thousands of developers, DevOps and SecOps users across dozens of organizations using the company’s suite of products. The big reference company right now is Priceline, but he says there are other big names that would prefer not to be public about it.
The company currently has 30 employees, with plans to double that by the end of the year, and he says that building diversity and inclusion into the hiring process is part of the company’s core values, and part of how the executive team gets measured.
“We’re big believers in putting our money where our mouth is and one of the OKRs for me and my co-founder [CEO Prakash Linga], or one of the things that we’re actually compensated for, is how well we are doing in building diversity and inclusion on the team,” he said. He adds that the recruiters that they are using are also being held to the same standard when it comes to providing a diverse set of candidates for open positions.
The company launched in 2018 and the founding team came from Vera, a startup that helped secure documents in motion. That company was sold to HelpSystems in December 2020 after Arora and Linga had left to start BluBracket.
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Cybersecurity startup Panaseer raises $26.5M Series B led by AllegisCyber Capital
Panaseer, which takes a data science approach to cybersecurity, has raised $26.5 million in a Series B funding led by AllegisCyber Capital. Existing investors, including Evolution Equity Partners, Notion Capital, AlbionVC, Cisco Investments and Paladin Capital Group, as well as new investor National Grid Partners, also participated. Panaseer has now raised $43 million to date.
Panaseer’s special sauce and sales pitch amount to what it calls “Continuous Controls Monitoring” (CCM). In plainer English that means correlating a great deal of data from all available security tools to check assets, control gaps, you name it.
As a result, the company says it can identify zero-day and other exposures faster, or exposure to, say, FireEye or SolarWinds vulnerabilities.
Jonathan Gill, CEO, Panaseer said: “Most enterprises have the tools and capability to theoretically prevent a breach from occurring. However, one of the key reasons that breaches occur is that there is no technology to monitor and react to failed controls. CCM continuously validates and measures levels of protection and provides notifications of failures. Ultimately, CCM enables these failures to be fixed before they become security incidents.”
Speaking to me on a call he added: “The investment, allows us to scale our organization to meet those demands of customers with a team of people to implement the platform and help them get tremendous value and to evolve the product. To add more and more capability to that technology to support more and more use cases. So they’re the two main directions, and there’s a market we think of tens of thousands of organizations of a certain size, who are regulated or they have assets worth protecting and a level of complexity that makes it difficult to solve the problem themselves. And our Advisory Board and the customers I’ve spoken with think maybe there are barely 20 companies in the world who can solve this problem. And everybody else gets stuck on the fact that it’s a really difficult data science problem to solve. So we want to scale that and take that to more organizations.”
And why did they pick these investors: “I think we picked them and they picked us, we’ve been on that journey together. It takes months to find the best combination. The dollars are all the same when it comes to investors, but I think they can help improve as an organization and grow just like the existing investors do. They give us access and reach into parts of the market and help make us better as organizations as well.”
Bob Ackerman, founder and managing director of AllegisCyber Capital, and co-founder of DataTribe said: “The emergence of Continuous Controls Monitoring as a new cybersecurity category demonstrates a ‘coming of age’ for cybersecurity. Cyber is the existential threat to the global digital economy. All levels of the enterprise, from the CISO, to Chief Risk Officer, to the Board of Directors are demanding comprehensive visibility, transparency and hard metrics to assess cyber situational awareness.”
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Cape Privacy announces $20M Series A to help companies securely share data
Cape Privacy, the early-stage startup that wants to make it easier for companies to share sensitive data in a secure and encrypted way, announced a $20 million Series A today.
Evolution Equity Partners led the round with participation from new investors Tiger Global Management, Ridgeline Partners and Downing Lane. Existing investors Boldstart Ventures, Version One Ventures, Haystack, Radical Ventures and a slew of individual investors also participated. The company has now raised approximately $25 million, including a $5 million seed investment we covered last June.
Cape Privacy CEO Ché Wijesinghe says that the product has evolved quite a bit since we last spoke. “We have really focused our efforts on encrypted learning, which is really the core technology, which was fundamental to allowing the multi-party compute capabilities between two organizations or two departments to work and build machine learning models on encrypted data,” Wijesinghe told me.
Wijesinghe says that a key business case involves a retail company owned by a private equity firm sharing data with a large financial services company, which is using the data to feed its machine learning models. In this case, sharing customer data, it’s essential to do it in a secure way and that is what Cape Privacy claims is its primary value prop.
He said that while the data sharing piece is the main focus of the company, it has data governance and compliance components to be sure that entities sharing data are doing so in a way that complies with internal and external rules and regulations related to the type of data.
While the company is concentrating on financial services for now, because Wijesinghe has been working with these companies for years, he sees uses cases far beyond a single vertical, including pharmaceuticals, government, healthcare telco and manufacturing.
“Every single industry needs this and so we look at the value of what Cape’s encrypted learning can provide as really being something that can be as transformative and be as impactful as what SSL was for the adoption of the web browser,” he said.
Richard Seewald, founding and managing partner at lead investor Evolution Equity Partners likes that ability to expand the product’s markets. “The application in Financial Services is only the beginning. Cape has big plans in life sciences and government where machine learning will help make incredible advances in clinical trials and counter-terrorism for example. We anticipate wide adoption of Cape’s technology across many use cases and industries,” he said.
The company has recently expanded to 20 people and Wijesinghe, who is half Asian, takes DEI seriously. “We’ve been very, very deliberate about our DEI efforts, and I think one of the things that we pride ourselves in is that we do foster a culture of acceptance, that it’s not just about diversity in terms of color, race, gender, but we just hired our first nonbinary employee,” he said,
Part of making people feel comfortable and included involves training so that fellow employees have a deeper understanding of the cultural differences. The company certainly has diversity across geographies with employees in 10 different time zones.
The company is obviously remote with a spread like that, but once the pandemic is over, Wijesinghe sees bringing people together on occasion with New York City as the hub for the company, where people from all over the world can fly in and get together.
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Quantexa raises $64.7M to bring big data intelligence to risk analysis and investigations
The wider field of cybersecurity — not just defending networks, but identifying fraudulent activity — has seen a big boost in activity in the last few months, and that’s no surprise. The global health pandemic has led to more interactions and transactions moving online, and the contractions we’re feeling across the economy and society have led some to take more desperate and illegal actions, using digital challenges to do it.
Today, a U.K. company called Quantexa — which has built a machine learning platform branded “Contextual Decision Intelligence” (CDI) that analyses disparate data points to get better insight into nefarious activity, as well as to (more productively) build better profiles of a company’s entire customer base — is raising a growth round of funding to address that opportunity.
The London-based startup has picked up $64.7 million, a Series C it will be using to continue building out both its tools and the use cases for applying them, as well as expanding geographically, specifically in North America, Asia-Pacific and more European territories.
The mission, said Vishal Marria, Quantexa’s founder and CEO, is to “connect the dots to make better business decisions.”
The startup built its business on the back of doing work for major banks and others in the financial services sector, and Marria added that the plan will be to continue enhancing tools for that vertical while also expanding into two growing opportunities: working with insurance and government/public sector organizations.
The backers in this round speak to how Quantexa positions itself in the market, and the traction it’s seen to date for its business. It’s being led by Evolution Equity Partners — a VC that specialises in innovative cybersecurity startups — with participation also from previous backers Dawn Capital, AlbionVC, HSBC and Accenture, as well as new backers ABN AMRO Ventures. HSBC, Accenture and ABN AMRO are all strategic investors working directly with the startup in their businesses.
Altogether, Quantexa has “thousands of users” across 70+ countries, it said, with additional large enterprises, including Standard Chartered, OFX and Dunn & Bradstreet.
The company has now raised some $90 million to date, and reliable sources close to the company tell us that the valuation is “well north” of $250 million — which to me sounds like it’s between $250 million and $300 million.
Marria said in an interview that he initially got the idea for Quantexa — which I believe may be a creative portmanteau of “quantum” and “context” — when he was working as an executive director at Ernst & Young and saw “many challenges with investigations” in the financial services industry.
“Is this a money launderer?” is the basic question that investigators aim to answer, but they were going about it, “using just a sliver of information,” he said. “I thought to myself, this is bonkers. There must be a better way.”
That better way, as built by Quantexa, is to solve it in the classic approach of tapping big data and building AI algorithms that help, in Marria’s words, connect the dots.
As an example, typically, an investigation needs to do significantly more than just track the activity of one individual or one shell company, and you need to seek out the most unlikely connections between a number of actions in order to build up an accurate picture. When you think about it, trying to identify, track, shut down and catch a large money launderer (a typical use case for Quantexa’s software) is a classic big data problem.
While there is a lot of attention these days on data protection and security breaches that leak sensitive customer information, Quantexa’s approach, Marria said, is to sell software, not ingest proprietary data into its engine to provide insights. He said that these days deployments typically either are done on premises or within private clouds, rather than using public cloud infrastructure, and that when Quantexa provides data to complement its customers’ data, it comes from publicly available sources (for example, Companies House filings in the U.K.).
There are a number of companies offering services in the same general area as Quantexa. They include those that present themselves more as business intelligence platforms that help detect fraud (such as Looker) through to those that are secretive and present themselves as AI businesses working behind the scenes for enterprises and governments to solve tough challenges, such as Palantir, through to others focusing specifically on some of the use cases for the technology, such as ComplyAdvantage and its focus on financial fraud detection.
Marria says that it has a few key differentiators from these. First is how its software works at scale: “It comes back to entity resolution that [calculations] can be done in real time and at batch,” he said. “And this is a platform, software that is easily deployed and configured at a much lower total cost of ownership. It is tech and that’s quite important in the current climate.”
And that is what has resonated with investors.
“Quantexa’s proprietary platform heralds a new generation of decision intelligence technology that uses a single contextual view of customers to profoundly improve operational decision making and overcome big data challenges,” said Richard Seewald, founding and managing partner of Evolution, in a statement. “Its impressive rapid growth, renowned client base and potential to build further value across so many sectors make Quantexa a fantastic partner whose team I look forward to working with.” Seewald is joining the board with this round.
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