The Stack

One to Watch #8: WCKD RZR’s Chuck Teixeira on revolutionising data access in multinationals

Chuck Teixeira, founder, WKD RZR.

More than a decade ago, a friend of Chuck Teixeira’s took him to a famous psychic in New York on a night out. “I was kind of sceptical” he tells The Stack: “But I had this conversation with the psychic and they said, ‘one day you’re going to run a technology company, you’re going to be involved in technology’. I said ‘there’s no chance – I’m a banker. Never, never, never, never, never!’ And then 10 years later, here we are…”

Mystic Meg was right. Teixeira, a former Chief Administrative Officer at HSBC is now the founder of WCKD RZR, a startup developing technology to automate global data governance compliance using machine learning. This week he secured $1.2 million in pre-seed funding from angel investors. While Teixeira might not have expected to be leading a tech startup, he had long thought about running his own business, but “I never really had the specific idea” he says modestly. But in his years in banking (Teixeira has also worked as Global COO, Capital & Liquidity Management Group at Barclays, and as COO at Nomura Securities) that idea imposed itself…

We’re making WCKD RZR The Stack’s latest “One to Watch”: a feature that highlights a startup we believe could become a critical contributor to the enterprise technology stack. (We’ve previously featured Firebolt, Persefoni, Enveil, Cutover, Element, StreamNative, and SkopeAI; many have gone on to large raises.)

One to Watch: Top Goldman quant’s new AI investment platform “SkopeAI”

During his four years at HSBC as Chief Administrative Officer and Head of Transformation, Global Banking Markets — with the bank under a deferred prosecution agreement and “regulators breathing down our necks” — Teixeira was searching for something to help automate the onerous process of collating 10 PB of data from 1.6 million clients across 65 different jurisdictions and keeping it compliant. But there was no solution.

“I was just really frustrated, and I was very public about it – I was in the press, I was speaking at conferences, saying, where are these solutions? I couldn’t find them. Talking to my peers and the other banks, everybody else was faced with the exact same situation,” Teixeira tells The Stack. “Because if you think about it, we were all spending hundreds of millions of dollars doing these big cloud transformations, with this promise that at the end all your data will be in one place, you’d be able to have access to it. And that’s not actually the case.”

(At HSBC his team ultimately pulled together tens of thousands of tables of information into an on-premises Hadoop environment, working with a machine learning specialist to measure the data quality coming in on five different dimensions; accuracy, completeness, uniqueness, validity and consistency and then use ML to link transactions across disparate client identifiers and started using it for financial crime use cases; with the idea of moving beyond that to start generating new client service use cases powered by AI…)

Chuck Teixeira with Rzor as a puppy.

WCKD RZR’s Data Watchdog hits beta testing

After years of talking about solving this problem himself and launching a product, a friend told him, using a crude but effective toilet-related aphorism Teixeira declines to provide for publication, to put up or shut up. He bit the bullet — “it took me this long to have the courage of my convictions as it were” he says — and WCKD RZR is now beta testing its first product, Data Watchdog. (The firm is named for Rzor, one of Teixeira’s beloved French Bulldogs, whose image also adorns the company’s logo.)

Data Watchdog is what Teixeira calls “data enablement” software: a middleware which sits between an organisation’s databases and catalogues the data in them. It then allows users to find, govern and access the data, while remaining compliant across different legal jurisdictions. Finding the data is the first challenge, Teixeira explains: “You don’t know what data you have, right? You’ve got all these different databases, it’s filled with data, but you don’t know what’s there. And so you need some way of actually having a map of that data, and having that labelled, so you can search for it.”

Next is governance: “That data is sitting on all these different jurisdictions, different countries, they’re all subject to different rules around data sharing data privacy. And then if you’re in financial services, there are financial regulations around it around, especially things like what’s public versus private side.”

Data Watchdog aims to build a map of these data sources and implement access policies depending on data type, jurisdiction and other factors – and do this automatically, using machine learning.

WCKD RZR founder: Data access is still a “horrific process…”

Finally, and potentially most excitingly for putative customers, is access: “Companies have all these horrible manual controls around trying to ensure that people are complying with those regulations.

“So let’s say you want to build a new data science use case, you want to build a new app, you want to implement a new system or regulation – you’ve got to go find the data, and then you want access to it. And what happens is you’ve got to go to all these legal compliance functions and say, hey, can I get permission to use this data? And it’s just a horrific process,” Teixeira explains. His former employer would spend more than $10m a year on data sharing approvals alone. And with each approval process taking months to complete, “what ends up happening is you sort of give up” as data science teams which should be working on dozens of projects wait for approvals.

“Unless the use case is so super important, and it’s such a priority for the business that it’s worth the pain of getting all these approvals, they’re like, you know what, let’s just put it on the back burner, and if we get around to it, and we can get the approvals, we’ll do it”, he says with a grimace that suggests hard experience.

This is where Data Watchdog comes into its own; WCKD RZR says the software is easily installed onto an organisation’s network allowing the data to remain where it was, and begins work in minutes. It spiders and maps all the company’s databases, with proprietary machine learning technology auto-labelling the data so that it can be easily accessed “Because the whole process is automated, it means that you can start to work on this data science or analytics use case immediately, not waiting months” says Teixeira.

Sweat and tears and tantrums

Listening to this, it seems extraordinary that a solution to this problem hasn’t been developed before now, given the financial services industry is not famed for willingly leaving money on the table. Teixeira says the challenge has been to break through vendor silos, whether it’s Oracle, SAP and PeopleSoft, or Azure, AWS and GCP: “The underlying technology has changed, but the methodology and the approach hasn’t.”

Figuring out how to connect all these different packages, databases and platforms has been the source of “sweat and tears and tantrums over the past couple of years” he says. Along with building out the technology of Data Watchdog, WCKD RZR has also refined the product’s scope through ongoing industry conversations – for example, by putting greater focus on the “access” elements, where before it was more focused on compliance.

One to Watch: NSA cryptographer’s data privacy startup Enveil

Coming from a banking background, Teixeira’s initial focus has been on financial services – but he’s also looking at applications in the pharmaceutical, retail and public sectors for Data Watchdog: “You’re doing lots of trials, lots of data, heavily regulated. And now as you try to get organisations to start sharing the data and trial results, you’re dealing with many types of encumbrances around who should have access, what you can see, you don’t want to identify patient names, things like that,” says Teixeira about the potential for Data Watchdog in pharma.

The future is access

And beyond Data Watchdog, WCKD RZR is working on a “data mesh” product – keeping data where it is, but pulling multiple data sets together to work as one homogenous set. For now, the focus is on getting Data Watchdog ready for launch, and potentially looking at a Series A round in a year or so’s time to build up the company’s sales and distribution infrastructure as well as continue working on product development.

The startup experience meanwhile has been a “rollercoaster” according to Teixeira, not least thanks to timing. He started pitching Data Watchdog early in 2020, so found himself going from 20 flights over three months to Zoom calls and remote hiring – an experience he’s written about for The Stack. But even with the lows of the pandemic or getting rejection he’s still loving it: “The highs are great, when you celebrate each of these successes, whether or not it’s raising the money, getting traction with clients, the feedback, those types of things. When we did the launch of the Alpha release of the product, and it was a case of it’s real, it works! People are seeing it, and this idea that you had, that you’ve now put it into real life,” that’s a great feeling, he says.

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