Avo, a startup that helps businesses better manage their data quality across teams, today announced that it has raised a $3 million seed round led by GGV Capital, with participation from  Heavybit, Y Combinator and others.

The company’s founder, Stefania Olafsdóttir, who is currently based in Iceland, was previously the head of data science at QuizUp, which at some point had 100 million users around the world. “I had the opportunity to build up the Data Science Division, and that meant the cultural aspect of helping people ask and answer the right questions — and get them curious about data — but it also meant the technical part of setting up the infrastructure and tools and pipelines, so people can get the right answers when they need it,” she told me. “We were early adopters of self-serve product analytics and culture — and we struggled immensely with data reliability and data trust.”

Image Credits: Avo

As companies collect more data across products and teams, the process tends to become unwieldy and different teams end up using different methods (or just simply different tags), which creates inefficiencies and issues across the data pipeline.

“At first, that unreliable data just slowed down decision making, because people were just like, didn’t understand the data and needed to ask questions,” Olafsdóttir said about her time at QuizUp. “But then it caused us to actually launch bad product updates based on incorrect data.” Over time, that problem only became more apparent.

“Once organizations realize how big this issue is — that they’re effectively flying blind because of unreliable data, while their competition might be like taking the lead on the market — the default is to patch together a bunch of clunky processes and tools that partially increase the level of liability,” she said. And that clunky process typically involves a product manager and a spreadsheet today.

At its core, the Avo team set out to build a better process around this, and after a few detours and other product ideas, Olafsdóttir and her co-founders regrouped to focus on exactly this problem during their time in the Y Combinator program.

Avo gives developers, data scientists and product managers a shared workspace to develop and optimize their data pipelines. “Good product analytics is the product of collaboration between these cross-functional groups of stakeholders,” Olafsdóttir argues, and the goal of Avo is to give these groups a platform for their analytics planning and governance — and to set company-wide standards for how they create their analytics events.

Once that is done, Avo provides developers with typesafe analytics code and debuggers that allows them to take those snippets and add them to their code within minutes. For some companies, this new process can help them go from spending 10 hours on fixing a specific analytics issue to an hour or less.

Most companies, the team argues, know — deep down — that they can’t fully trust their data. But they also often don’t know how to fix this problem. To help them with this, Avo also today released its Inspector product. This tool processes event streams for a company, visualizes them and then highlights potential errors. These could be type mismatches, missing properties or other discrepancies. In many ways, that’s obviously a great sales tool for a service that aims to avoid exactly these problems.

One of Avo’s early customers is Rappi, the Latin American delivery service. “This year we scaled to meet the demand of 100,000 new customers digitizing their deliveries and curbside pickups. The problem with every new software release was that we’d break analytics. It represented 25% of our Jira tickets,” said Rappi’s head of Engineering, Damian Sima. “With Avo we create analytics schemas upfront, identify analytics issues fast, add consistency over time and ensure data reliability as we help customers serve the 12+ million monthly users their businesses attract.”

As most startups at this stage, Avo plans to use the new funding to build out its team and continue to develop its product.

“The next trillion-dollar software market will be driven from the ground up, with developers deciding the tools they use to create digital transformation across every industry. Avo offers engineers ease of implementation while still retaining schemas and analytics governance for product leaders,” said GGV Capital Managing Partner Glenn Solomon. “Our investment in Avo is an investment in software developers as the new kingmakers and product leaders as the new oracles.”

Oracle was never fond of the JEDI cloud contract process, that massive $10 billion, decade-long Department of Defense cloud contract that went to a single vendor. It was forever arguing to anyone who would listen that that process was faulty and favored Amazon.

Yesterday it lost another round in court when the U.S. Court of Appeals rejected the database giant’s argument that the procurement process was flawed because it went to a single vendor. It also didn’t buy that there was a conflict of interest because a former Amazon employee was involved in writing the DoD’s request for proposal criteria.

On the latter point, the court wrote, “The court addressed the question whether the contracting officer had properly assessed the impact of the conflicts on the procurement and found that she had.”

Further, the court found that Oracle’s case didn’t have merit in some cases because it failed to meet certain basic contractual criteria. In other cases, it didn’t find that the DoD violated any specific procurement rules with this bidding process.

This represents the third time the company has tried to appeal the process in some way, four if you include direct executive intervention with the president. In fact, even before the RFP had been released in April 2018, CEO Safra Catz brought complaints to the president that the bid favored Amazon.

In November 2018, the Government Accountability Office (GAO) denied Oracle’s protest that it favored Amazon or any of the other points in their complaint. The following month, the company filed a $10 billion lawsuit in federal court, which was denied last August. Yesterday’s ruling is on the appeal of that decision.

It’s worth noting that for all its complaints that the deal favored Amazon, Microsoft actually won the bid. Even with that determination, the deal remains tied up in litigation as Amazon has filed multiple complaints, alleging that the president interfered with the deal and that they should have won on merit.

As with all things related to this contract, the drama has never stopped.

A newly discovered bug in a cloud system used to manage SonicWall firewalls could have allowed hackers to break into thousands of corporate networks.

Enterprise firewalls and virtual private network appliances are vital gatekeepers tasked with protecting corporate networks from hackers and cyberattacks while still letting in employees working from home during the pandemic. Even though most offices are empty, hackers frequently look for bugs in critical network gear in order to break into company networks to steal data or plant malware.

Vangelis Stykas, a researcher at security firm Pen Test Partners, found the new bug in SonicWall’s Global Management System (GMS), a web app that lets IT departments remotely configure their SonicWall devices across the network.

But the bug, if exploited, meant any existing user with access to SonicWall’s GMS could create a user account with access to any other company’s network without permission.

From there, the newly created account could remotely manage the SonicWall gear of that company.

In a blog post shared with TechCrunch, Stykas said there were two barriers to entry. Firstly, a would-be attacker would need an existing SonicWall GMS user account. The easiest way — and what Stykas did to independently test the bug — was to buy a SonicWall device.

The second issue was that the would-be attacker would also need to guess a unique seven-digit number associated with another company’s network. But Stykas said that this number appeared to be sequential and could be easily enumerated, one after the other.

Once inside a company’s network, the attacker could deliver ransomware directly to the internal systems of their victims, an increasingly popular tactic for financially driven hackers.

SonicWall confirmed the bug is now fixed. But Stykas criticized the company for taking more than two weeks to patch the vulnerability, which he described as “trivial” to exploit.

“Even car alarm vendors have fixed similar issues inside three days of us reporting,” he wrote.

A SonicWall spokesperson defended the decision to subject the fix to a “full” quality check before it was rolled out, and said it is “not aware” of any exploitation of the vulnerability.

Process automation startup Hypatos has raised a €10 million (~$11.8 million) seed round of funding from investors including Blackfin Tech, Grazia Equity, UVC Partners and Plug & Play Ventures.

The Germany and Poland-based company was spun out of AI for accounting startup Smacc at the back end of 2018 to apply deep learning tech to power a wider range of back-office automation, with a focus on industries with heavy financial document processing needs, such as the financial and insurance sectors.

Hypatos is applying language processing AI and computer vision tech to speed up financial document processing for business use cases such as invoices, travel and expense management, loan application validation and insurance claims handling via — touting a training data set of more than 10 million annotated data entities.

It says the new seed funding will go on R&D to expand its portfolio of AI models so it can automate business processing for more types of documents, as well as for fueling growth in Europe, North American and Asia. Its customer base at this point includes Fortune 500 companies, major accounting firms and more than 300 software companies.

While there are plenty of business process automation plays, Hypatos says its use of deep learning tech supports an “in-depth understanding” of document content — which in turn allows it to offer customers a “soup to nuts” automation menu that covers document classification, information capturing, content validation and data enrichment.

It dubs its approach “cognitive process automation” (CPA) versus more basic applications of business process automation with software robots (RPA), which it argues aren’t so contextually savvy — thereby claiming an edge.

As well as document processing solutions, it has developed machine learning modules for enhancing customers’ existing systems (e.g. ECM, ERP, CRM, RPA); and offers APIs for software providers to draw on its machine learning tech for their own applications.

“All offerings include machine learning pipeline software for continuous model training in the cloud or in on-premise deployments,” it notes in a press release.

“We have deep knowledge of how financial documents are processed and millions of data entities in our training data,” says chief commercial officer Cem Dilmegani, discussing where Hypatos fits in the business process automation landscape. “We get compared to RPA companies like UiPath, enterprise content management (ECM) companies like Kofax Readsoft as well as generalist ML document automation companies like Hyperscience. However, we are quite different.

“We focus on end-to-end automation, we don’t only help companies capture data, we help them process it using our deep domain understanding, enabling higher rates of automation. For example, to automate incoming invoice processing (A/P automation) we apply our document understanding AI to capture all data, classify the document, identify the specific goods and services, validate for internal/external compliance and assign financial accounts, cost centers, cost categories etc. to automate all processing tasks.

“Finally, we offer this technology as components easily accessible via APIs. This allows RPA or ECM users to leverage our technology and increase their level of automation.”

Hypatos claims it’s seeing uplift as a result of the coronavirus pandemic — noting it’s providing a service to more than a dozen Fortune 500 companies to help with in-shoring efforts, which it says are accelerating as a result of COVID-19 putting pressure on the traditional business process outsourcing model as offshore workforce productivity in lower wage regions is affected by coronavirus lockdowns.

“We believe that we are in a pivotal moment of machine learning adoption in large organizations,” adds Andreas Unseld, partner at UVC Partners, in a supporting statement. “Hypatos’ technology provides ample opportunity to transform many core business processes. We’re impressed by the Hypatos machine learning technology and see the team in a perfect position to take a leading role in the machine learning revolution to come.”