When it comes to geospatial and mapping data and how they are leveraged by organizations, satellites continue to play a critical role when it comes to sourcing raw information.  Getting that raw data into a state that can be usable by enterprises, however, is a different story. Today, a Berlin-based startup called LiveEO, which has built a satellite analytics platform to do just that, has raised €19 million ($19.5 million) on the back of strong demand for its tech from companies working in transportation and energy infrastructure.

The rise of companies like LiveEO comes on the back of a period of rapid commercialization in infrastructure intended to be used in space, typified by companies like SpaceX but also others building, for example, a new wave of satellites themselves. As with the larger opportunity in enterprise IT, big data players like LiveEO are essentially the second wave of that development: applications built leveraging that infrastructure.

Image Credits: LiveEO (opens in a new window) under a CC BY 2.0 (opens in a new window) license.

“Someone has to build applications for end users to really make it simple to use and integrate that data into processes,” explained Daniel Seidel (left), who co-founded and co-leads LiveEO with Sven Przywarra (right). “That is what we are doing at scale.”

MMC Ventures is leading the investment, a Series B, and in addition to €17M of venture capital, the round also includes backing from two public bodies, the European Commission and Investitionsbank Berlin. Previous backers Dieter von Holtzbrinck Ventures (DvH Ventures), Helen Ventures, Matterwave, and motu ventures, and new backers Segenia Capital and Hannover Digital Investments (HDInv), are also participating. LiveEO had previously raised €5.25 million Series A in 2021, and it said that in that time, it’s tripled revenues with customers in five continents and more than doubled its headcount to about 100, with more than half of those engineers and data scientists.

As a German startup, LiveEO is one of a small but growing group of startups in Europe capitalizing on increasing interest in space among investors in recent years, despite the wider pressures on tech finance. Relatively speaking, though, the sums are still modest compared with other areas of tech: LiveEO says that this €19 million round is one of the largest in earth observation tech in Europe. LiveEO is focused on enterprise, specifically industrial applications for its analytics — although given the geopolitical landscape, and how that is bringing a new host of interested parties playing the part of financiers to foster its growth, it will be interesting to see how that develops.

LiveEO’s platform addresses a specific gap between space tech and enterprise data. Satellites are collectively producing more data about our world than ever before, covering not just physical objects in the most minute detail, but thermal progressions, how systems are moving, and more.

Ironically, a lot of that data is very locked up when it comes to enterprises using it: given the fragmentation in the satellite industry itself, the data is not only often in very raw, formats, but coming from multiple sources, too, so getting it into forms that can be integrated into existing IT systems and specifically (and more trickily) the IT systems that integrate with the infrastructure that is the building block of a lot of industrial deployments — let alone parsing it for insights — are all tall tasks, so much so that the opportunities of doing them often go unrealized.

The core of the company’s platform brings all this together, in what LiveEO describes as an “infrastructure monitoring suite powered by satellite imagery.” This involves taking the earth observation data produced by satellites and applying AI to it to analyze it in the context of what LiveEO’s industrial clients — which include major railway companies like Deutsche Bahn, or the energy company e.on — are seeking to understand better.

That could include data on risks from vegetation on railways or other lines; ground deformation; or other physical movements or activities; and it also includes the ability for an LiveEO user to directly integrate this data to link up with its own IT management systems for its infrastructure, for example those that monitor systems to make sure they are working as they should. It also pitches its solution as greener: using satellites to source the kind of geographic data that these industrial applications need means no need to use on-the-ground teams and vehicles to source it in other ways.

“One of the great advantages of satellite data is that we don’t require hardware to be installed at the infrastructure itself,” said Przywarra.

That data, they believe, is also more complete: as Seidel describes it, the combination of terabytes of data from multiple sources means it is not just 3D, but “4D” — with thermal and other kinds of details available, “is like the difference between using an image from a smartphone, and a high-end camera with high resolution.”

All of this is also still a relatively new field, Przywarra added. “Prior to Google Earth, satellite maps were only used by experts,” he said. “We enable more non-experts to use satellite data. We make it accessible and usable.”

Lead investor MMC is one of the more prominent deep tech investors in Europe, and it’s notable that they’re putting focus in this area as an opportunity.

“We are excited to lead this round for LiveEO and it reflects MMC’s continued focus on emerging datasets and companies that develop AI analytics to power core business decisions,” said Andrei Dvornic, a principal at MMC Ventures, in a statement. “LiveEO offers a critical tool that paves the way for sustainable industry automation, and we wholeheartedly support the company’s vision of leveraging satellite technologies, big data, and the latest developments in artificial intelligence to help companies adapt to the challenges posed by climate change.”

Data quality has been shaping up as a salient and increasingly critical part of the world of data science: enterprises are sitting on growing troves of information, but it’s only useful if we can trust it to be accurate and usable. To that end, Validio, a startup building tools to improve and ensure data quality — specifically with tools that let users clean up data both stored in data warehouses and elsewhere, as well as in real-time — is announcing a seed round to mark its emergence from stealth. The Stockholm-based company has raised $15 million, funding that it plans to use for business and product development, R&D and to hire more talent.

Lakestar — the London-based VC that made early investments in companies like Facebook and Airbnb but has largely focused on backing promising-looking startups out of Europe (it also backed Skype, Spotify, Revolut and many others) — led this round, with J12 and several high profile individuals also participating.

(The list includes footballer (soccer player) Zlatan Ibrahimović, Snowflake’s CMO Denise Persson, MongoDB’s co-founder Kevin Ryan, Neo4j co-founder Emil Eifrem, DeepMind’s head of product Mehdi Ghissassi and Kim Fai Kok & Dara Gill of angel collective Framtid.)

As with a lot of enterprise startups in stealth these days, Validio has been using the time since being founded in 2019 to work quietly on its product while also signing up customers for live deployments. Its clients range across the usual suspects in the big data game — those in marketing and commerce, security companies, and business intelligence. Validio doesn’t disclose a lot of names but notes a few: Budbee and Babyshop in the e-commerce space; e-scooter company Voi; and electricity startup Tibber.

The challenge that Validio has identified an is addressing is one that CEO and co-founder Patrik Liu Tran said he encountered early on in his working life. A math and computer wiz, he graduated aged 16 from school and also accelerated his time at university, going to work in 2014/2015 while still a teenager consulting companies on AI projects. It was still a nascent endeavor in most places (frankly, it still is), and one of the big issues, apart from having few in the field prepared to go into companies to work on their problems, was the lack of integrity and quality in the data that they were trying to use in their machine learning models, he said.

“At every company that I was advising, the thing that caught my attention was the lack of trust in data, so much that people did very little with it, and there were no tools really to help with that,” he said in an interview. He added that the first efforts in identifying the issue and trying to deal with it (such as the Great Expectations open source project, created by the people who are behind Superconductive), were promising but do not focus on real-time information as much as data in warehouses.

“But machine learning resides in streams, not the warehouse,” he said. 

Beyond that, they are generally too reliant on rules that engineers and data scientists need to set and regularly monitor and tweak.

Validio’s approach is to create not exactly low code tools. “We’re building for data engineers. It’s very technical,” Tran said, slightly surprised with my question about that. “But we are focusing on a smooth user experience.”

That includes using machine learning and statistical analysis to “teach” a users’ system to find and respond more quickly to the data coming through the pipeline; sets of rules that are created automatically for an engineer to use or to complement with customized rules; automated thresholds and auto-resolution capabilities, and more.

“We want to make it as seamless as possible for data engineers to do their work,” he added.

The company doesn’t have a larger set of rules that it applies across the platform, but has built it to be tailored to individual organizations.

“‘Data quality’ is hard to define. What is good for one company might be bad for another,” Tran said. “Data is never perfect and companies also need to start to accept that.” But the list of its investors (including some of those attached to strategic names) is a sign that others may well be singing the same tune with that kind of thinking, and how Validio specifically is building to address that: tools to improve data quality, but built for the real world.

There are a few other companies that have identified the market for data quality and are building to address that — including Great Expectations creator Superconductive, which raised $40 million earlier this year; along with heavyweights like Microsoft, SAS, and Talend — but for now Validio’s approach is one that seems to be striking the right chord, enough to expand bets in what is still a young space.

“As data teams are increasingly shifting their focus toward data quality, we believe that Validio is uniquely positioned to become the next big global software player from Europe,” noted Stephen Nundy, Lakestar partner, in a statement. “Validio has built its platform with a unique architecture, enabling the management of data quality in data warehouses, lakes and streams both on the actual data and metadata in real-time. We look forward to supporting the stellar Validio team in their journey building a global data infrastructure leader.”

Airbyte, the well-funded open-source data integration platform, today announced that it has acquired Grouparoo, an open-source startup that focuses on helping businesses sync data between their data warehouses and cloud-based tools. In many ways, this complements Airbyte’s offering, which focuses on loading data into data warehouses, while Grouparoo then specializes in operationalizing that data.

“It’s an open source reverse ETL [extract, transform, load] company,” Airbyte co-founder and CEO Michel Tricot said. “They focus exactly on the other direction [from Airbyte]. They have a very strong technical team and they’ve already built a part of the product  and it’s going to be about how we can leverage everything that they’ve done and get them into the team to expand the Airbyte product for reverse ETL”

Image Credits: Airbyte

Tricot stressed that Aribyte here isn’t so much buying the product as the team’s expertise. “We’re not integrating their technology,” he said. “It’s more about the knowledge that they have and the experience that they’ve got.” Tricot also noted that the Grouparoo team always focused on making its service accessible to a non-technical audience, something Airbyte, too, has long focused on (though it also offers a command-line tool for technical users that want more flexibility, too). He specifically called out that he hopes the team can help Airbyte build out UI tools for creating the connectors it needs to connect to more third-party services.

Grouparoo CEO and co-founder Brian Leonard chose a slightly more sober tone in his announcement today.

“Thank you to our users and investors for your continued support,” he wrote. “Grouparoo certainly had a set of early believers and users that saw what we were trying to accomplish. They deployed Grouparoo in their infrastructure or on our cloud, and some even built their own plugins to extend the platform. When we really took a hard look at it, though, we were not on the right path to have the impact that we wanted to have in the world.”

He did note, though, that he believes Airbyte is on the right path, in part because virtually every company today needs to extract and load data into their warehouses if they want to operationalize it.

“By aligning with the engineers that are responsible for this core task, Airbyte has thrived. By being further down the value chain with a more varied set of stakeholders, Grouparoo saw less demand,” wrote Leonard.

The two companies did not disclose the price of the acquisition. Grouparoo previously raised about $3 million in a seed round led by Eniac Venture and Fuel Capital in late 2020.

Just over a year ago, Spotify co-founder Daniel Ek pledged 1 billion euros ($1.2 billion) of his personal fortune towards funding deeptech “moonshot projects”, spread across the next 10 years. In particular, he was most interested in boosting European tech and European entrepreneurs as he said they were typically underfunded compared to US counterparts.

Today it looks like he’s also out to boost European (and other) liberal democratic societies with the news that Prima Materia, his fund, will put €100m into Helsing, a European defence AI company, which has raised €102.5m in total as part of its Series A financing. The new funding will be used to grow the team of over 70 (so far), and accelerate product and delivery.

Following a seed round with European investors earlier this year, Helsing plans to use it’s AI platform to boost defence and national security among the afore-mentioned democracies by making them more efficient, using live data.

Ek will join the company’s Board, alongside Helsing’s co-founders Torsten Reil, Gundbert Scherf and Niklas Köhler.

Helsing says its real-time software platform “processes data from multiple sensors directly on vehicles and systems, to provide an integrated view of the operational environment with the aim of faster and more accurate decision-making.” So, unlike some systems which seek to make longer-term organisational changes, this appears to be a highly “live scenario” platform. This would be crucial in scenarios like cyber attacks, as well as ‘kinetic’ scenarios.

Helsing says this will involve turning unstructured sensor data into “information advantage” for democratic governments, providing the clearest picture possible in any operating environment by using “AI on the edge”. This, quite obviously, would involve gathering data from multiple sensors directly on vehicles and systems.

Helsing also says it will “focus on serving countries which meet the highest democratic standards.”

Founded in 2021 and with offices in London, Munich and Berlin, Helsing plans to serve several countries, starting with teams in the UK, France and Germany. It recently appointed former senior UK MoD official Nick Elliott as CEO of Helsing UK, and Sir Chris Deverell (formerly head of the UK’s Joint Forces Command) as a senior advisor. A French entity will be a third home market in early 2022. Robert Fink joined as CTO from Palantir, where he was Chief Architect, earlier this year.

In a statement, Torsten Reil, Co-founder and CEO, said: “We founded Helsing with the conviction that liberal democratic values are worth defending, and that artificial intelligence will be an essential capability to keep us safe. Unlike authoritarian regimes, democratically elected governments have a special responsibility to their citizens: the use of technology needs to be transparent and guided by ethical standards set by us all. We believe that the required control and accountability needs to be designed into the technology from the outset.”

Gundbert Scherf, Co-founder and COO/President, added: “Working like a software and tech company, we designed Helsing to overcome another key challenge all democratic governments face: Government works in linear processes that are inherently difficult to square with the exponential speed of technology. At Helsing we don’t wait for the specific requirement to come out of the process, but instead invest our own resources into our platform to solve entire categories of problems.”

A word about the team: Reil previously built NaturalMotion, which exited to Zynga for $527m. Scherf (President/ COO) was previously Partner at McKinsey & Company and Architect of the Bundeswehr’s Cyber and Information Domain Command and the digital directorate-general at the German Ministry of Defence. Koehler (CPO) is a Theoretical Physicist and has published AI contributions in Nature, Nature Communications, Nature Machine Intelligence. Fink (CTO) was a software engineer at Palantir Technologies. Elliott CBE MBE (CEO Helsing UK) was recently Director General of the UK Vaccine Taskforce.

Daniel Ek commented: “We founded Prima Materia to advance ambitious science and technology to solve the world’s biggest challenges and help society progress towards a better future… Europe has a tremendous opportunity to lead in building dynamic AI systems in an ethical, transparent, and responsible manner. Torsten, Gundbert, Niklas, and the entire Helsing team take this responsibility seriously and are driven by the same values and ambition that led us to start Prima Materia.”

Census, a startup that helps businesses sync their customer data from their data warehouses to their various business tools like Salesforce and Marketo, today announced that it has raised a $16 million Series A round led by Sequoia Capital. Other participants in this round include Andreessen Horowitz, which led the company’s $4.3 million seed round last year, as well as several notable angles, including Figma CEO Dylan Field, GitHub CTO Jason Warner, Notion COO Akshay Kothari and Rippling CEO Parker Conrad.

The company is part of a new crop of startups that are building on top of data warehouses. The general idea behind Census is to help businesses operationalize the data in their data warehouses, which was traditionally only used for analytics and reporting use cases. But as businesses realized that all the data they needed was already available in their data warehouses and that they could use that as a single source of truth without having to build additional integrations, an ecosystem of companies that operationalize this data started to form.

The company argues that the modern data stack, with data warehouses like Amazon Redshift, Google BigQuery and Snowflake at its core, offers all of the tools a business needs to extract and transform data (like Fivetran, dbt) and then visualize it (think Looker).

Tools like Census then essentially function as a new layer that sits between the data warehouse and the business tools that can help companies extract value from this data. With that, users can easily sync their product data into a marketing tool like Marketo or a CRM service like Salesforce, for example.

Image Credits: Census

“Three years ago, we were the first to ask, ‘Why are we relying on a clumsy tangle of wires connecting every app when everything we need is already in the warehouse? What if you could leverage your data team to drive operations?’ When the data warehouse is connected to the rest of the business, the possibilities are limitless.” Census explains in today’s announcement. “When we launched, our focus was enabling product-led companies like Figma, Canva, and Notion to drive better marketing, sales, and customer success. Along the way, our customers have pulled Census into more and more scenarios, like auto-prioritizing support tickets in Zendesk, automating invoices in Netsuite, or even integrating with HR systems.“

Census already integrates with dozens of different services and data tools and its customers include the likes of Clearbit, Figma, Fivetran, LogDNA, Loom and Notion.

Looking ahead, Census plans to use the new funding to launch new features like deeper data validation and a visual query experience. In addition, it also plans to launch code-based orchestration to make Census workflows versionable and make it easier to integrate them into enterprise orchestration system.

Most developers don’t enjoy writing documentation for their code and that makes life quite a bit harder when a new team member tries to get started on working on a company’s codebase. And even when there are documentation or in-line comments in the source code, that’s often not updated and over time, that information becomes close to irrelevant. Swimm, which today announced that it has raised a $5.7 million seed round, aims to automate as much of this process as possible after the initial documentation has been written by automatically updating it as changes are made.

The funding round was led by Pitango First, with TAU Ventures, Axon Ventures and Fundfire also investing in this round, together with a group of angel investors that include the founder of developer platform Snyk.

Image Credits: Swimm

Swimm’s marketing mostly focuses on helping teams speed up onboarding, but it’s probably a useful tool for any team. Using Swimm, you can create the standard — but auto-updated — documentation, but also walkthroughs and tutorials. Using its code browser, you can also easily find all of the documentation that relates to a given file.

The nifty part here is that while the tool can’t write the documentation for you, Swimm will automatically update any code examples in the documentation for you — or alert you when there is a major change that needs a manual update. Ideally, this will reduce the drift between the codebase and documentation.

Image Credits: Swimm

The founding team, Oren Toledano (CEO), Omer Rosenbaum (CTO), Gilad Navot (Chief Product Officer) and Tom Ahi Dror (Chief Business Officer), started working on this problem based on their experience while running Israel Tech Challenge, a coding bootcamp inspired by the training program used by the Israeli Defence Forces’ 8200 Intelligence Unit.

“We met with many companies in Israel and in the US to understand the engineering onboarding process,” Toledano told me. “And we felt that it was kind of broken — and many times, we heard the sentence: ‘we throw them to the water, and they either sink or swim.'” (That’s also why the company is called Swimm). Companies, he argues, often don’t have a way to train new employees on their code base, simply because it’s impossible for them to do so effectively without good documentation.

“The larger the company is, the more scattered the knowledge on the code base is — and a lot of this knowledge leaves the company when developers leave,” he noted.

With Swimm, a company could ideally not just offer those new hires access to tutorials that are based on the current code base, but also an easier entryway to start working on the production codebase as well.

Image Credits: Swimm

One thing that’s worth noting here is that developers run Swimm locally on a developer’s machine. In part, that’s because this approach reduces the security risks since no code is ever sent to Swimm’s servers. Indeed, the Swimm team tells me that some of its early customers are security companies. It also makes it easier for new users to get started with Swimm.

Toledano tells me that while the team mostly focused on building the core of the product and working with its early design partners (and its first set of paying customers), the plan for the next few months is to bring on more users after launching the product’s beta.

“Software development is now at the core of every modern business. Swimm provides a structured, contextual and transparent way to improve developer productivity,” said Yair Cassuto, a partner at Pitango First who is joining Swimm‘s board. “Swimm’s solution allows for rapid and insightful onboarding on any codebase. This applies across the developer life cycle: from onboarding to project transitions, adopting new open source capabilities and even offboarding.”                                                                                   

Hightouch, a SaaS service that helps businesses sync their customer data across sales and marketing tools, is coming out of stealth and announcing a $2.1 million seed round. The round was led by Afore Capital and Slack Fund, with a number of angel investors also participating.

At its core, Hightouch, which participated in Y Combinator’s Summer 2019 batch, aims to solve the customer data integration problems that many businesses today face.

During their time at Segment, Hightouch co-founders Tejas Manohar and Josh Curl witnessed the rise of data warehouses like Snowflake, Google’s BigQuery and Amazon Redshift — that’s where a lot of Segment data ends up, after all. As businesses adopt data warehouses, they now have a central repository for all of their customer data. Typically, though, this information is then only used for analytics purposes. Together with former Bessemer Ventures investor Kashish Gupta, the team decided to see how they could innovate on top of this trend and help businesses activate all of this information.

HighTouch co-founders Kashish Gupta, Josh Curl and Tejas Manohar.

“What we found is that, with all the customer data inside of the data warehouse, it doesn’t make sense for it to just be used for analytics purposes — it also makes sense for these operational purposes like serving different business teams with the data they need to run things like marketing campaigns — or in product personalization,” Manohar told me. “That’s the angle that we’ve taken with Hightouch. It stems from us seeing the explosive growth of the data warehouse space, both in terms of technology advancements as well as like accessibility and adoption. […] Our goal is to be seen as the company that makes the warehouse not just for analytics but for these operational use cases.”

It helps that all of the big data warehousing platforms have standardized on SQL as their query language — and because the warehousing services have already solved the problem of ingesting all of this data, Hightouch doesn’t have to worry about this part of the tech stack either. And as Curl added, Snowflake and its competitors never quite went beyond serving the analytics use case either.

Image Credits: Hightouch

As for the product itself, Hightouch lets users create SQL queries and then send that data to different destinations  — maybe a CRM system like Salesforce or a marketing platform like Marketo — after transforming it to the format that the destination platform expects.

Expert users can write their own SQL queries for this, but the team also built a graphical interface to help non-developers create their own queries. The core audience, though, is data teams — and they, too, will likely see value in the graphical user interface because it will speed up their workflows as well. “We want to empower the business user to access whatever models and aggregation the data user has done in the warehouse,” Gupta explained.

The company is agnostic to how and where its users want to operationalize their data, but the most common use cases right now focus on B2C companies, where marketing teams often use the data, as well as sales teams at B2B companies.

Image Credits: Hightouch

“It feels like there’s an emerging category here of tooling that’s being built on top of a data warehouse natively, rather than being a standard SaaS tool where it is its own data store and then you manage a secondary data store,” Curl said. “We have a class of things here that connect to a data warehouse and make use of that data for operational purposes. There’s no industry term for that yet, but we really believe that that’s the future of where data engineering is going. It’s about building off this centralized platform like Snowflake, BigQuery and things like that.”

“Warehouse-native,” Manohar suggested as a potential name here. We’ll see if it sticks.

Hightouch originally raised its round after its participation in the Y Combinator demo day but decided not to disclose it until it felt like it had found the right product/market fit. Current customers include the likes of Retool, Proof, Stream and Abacus, in addition to a number of significantly larger companies the team isn’t able to name publicly.