Apr
06
2021
--

Aporia raises $5M for its AI observability platform

Machine learning (ML) models are only as good as the data you feed them. That’s true during training, but also once a model is put in production. In the real world, the data itself can change as new events occur and even small changes to how databases and APIs report and store data could have implications on how the models react. Since ML models will simply give you wrong predictions and not throw an error, it’s imperative that businesses monitor their data pipelines for these systems.

That’s where tools like Aporia come in. The Tel Aviv-based company today announced that it has raised a $5 million seed round for its monitoring platform for ML models. The investors are Vertex Ventures and TLV Partners.

Image Credits: Aporia

Aporia co-founder and CEO Liran Hason, after five years with the Israel Defense Forces, previously worked on the data science team at Adallom, a security company that was acquired by Microsoft in 2015. After the sale, he joined venture firm Vertex Ventures before starting Aporia in late 2019. But it was during his time at Adallom where he first encountered the problems that Aporio is now trying to solve.

“I was responsible for the production architecture of the machine learning models,” he said of his time at the company. “So that’s actually where, for the first time, I got to experience the challenges of getting models to production and all the surprises that you get there.”

The idea behind Aporia, Hason explained, is to make it easier for enterprises to implement machine learning models and leverage the power of AI in a responsible manner.

“AI is a super powerful technology,” he said. “But unlike traditional software, it highly relies on the data. Another unique characteristic of AI, which is very interesting, is that when it fails, it fails silently. You get no exceptions, no errors. That becomes really, really tricky, especially when getting to production, because in training, the data scientists have full control of the data.”

But as Hason noted, a production system may depend on data from a third-party vendor and that vendor may one day change the data schema without telling anybody about it. At that point, a model — say for predicting whether a bank’s customer may default on a loan — can’t be trusted anymore, but it may take weeks or months before anybody notices.

Aporia constantly tracks the statistical behavior of the incoming data and when that drifts too far away from the training set, it will alert its users.

One thing that makes Aporia unique is that it gives its users an almost IFTTT or Zapier-like graphical tool for setting up the logic of these monitors. It comes pre-configured with more than 50 combinations of monitors and provides full visibility in how they work behind the scenes. That, in turn, allows businesses to fine-tune the behavior of these monitors for their own specific business case and model.

Initially, the team thought it could build generic monitoring solutions. But the team realized that this wouldn’t only be a very complex undertaking, but that the data scientists who build the models also know exactly how those models should work and what they need from a monitoring solution.

“Monitoring production workloads is a well-established software engineering practice, and it’s past time for machine learning to be monitored at the same level,” said Rona Segev, founding partner at  TLV Partners. “Aporia‘s team has strong production-engineering experience, which makes their solution stand out as simple, secure and robust.”

 

Mar
10
2021
--

Aqua Security raises $135M at a $1B valuation for its cloud native security platform

Aqua Security, a Boston- and Tel Aviv-based security startup that focuses squarely on securing cloud-native services, today announced that it has raised a $135 million Series E funding round at a $1 billion valuation. The round was led by ION Crossover Partners. Existing investors M12 Ventures, Lightspeed Venture Partners, Insight Partners, TLV Partners, Greenspring Associates and Acrew Capital also participated. In total, Aqua Security has now raised $265 million since it was founded in 2015.

The company was one of the earliest to focus on securing container deployments. And while many of its competitors were acquired over the years, Aqua remains independent and is now likely on a path to an IPO. When it launched, the industry focus was still very much on Docker and Docker containers. To the detriment of Docker, that quickly shifted to Kubernetes, which is now the de facto standard. But enterprises are also now looking at serverless and other new technologies on top of this new stack.

“Enterprises that five years ago were experimenting with different types of technologies are now facing a completely different technology stack, a completely different ecosystem and a completely new set of security requirements,” Aqua CEO Dror Davidoff told me. And with these new security requirements came a plethora of startups, all focusing on specific parts of the stack.

Image Credits: Aqua Security

What set Aqua apart, Dror argues, is that it managed to 1) become the best solution for container security and 2) realized that to succeed in the long run, it had to become a platform that would secure the entire cloud-native environment. About two years ago, the company made this switch from a product to a platform, as Davidoff describes it.

“There was a spree of acquisitions by CheckPoint and Palo Alto [Networks] and Trend [Micro],” Davidoff said. “They all started to acquire pieces and tried to build a more complete offering. The big advantage for Aqua was that we had everything natively built on one platform. […] Five years later, everyone is talking about cloud-native security. No one says ‘container security’ or ‘serverless security’ anymore. And Aqua is practically the broadest cloud-native security [platform].”

One interesting aspect of Aqua’s strategy is that it continues to bet on open source, too. Trivy, its open-source vulnerability scanner, is the default scanner for GitLab’s Harbor Registry and the CNCF’s Artifact Hub, for example.

“We are probably the best security open-source player there is because not only do we secure from vulnerable open source, we are also very active in the open-source community,” Davidoff said (with maybe a bit of hyperbole). “We provide tools to the community that are open source. To keep evolving, we have a whole open-source team. It’s part of the philosophy here that we want to be part of the community and it really helps us to understand it better and provide the right tools.”

In 2020, Aqua, which mostly focuses on mid-size and larger companies, doubled the number of paying customers and it now has more than half a dozen customers with an ARR of over $1 million each.

Davidoff tells me the company wasn’t actively looking for new funding. Its last funding round came together only a year ago, after all. But the team decided that it wanted to be able to double down on its current strategy and raise sooner than originally planned. ION had been interested in working with Aqua for a while, Davidoff told me, and while the company received other offers, the team decided to go ahead with ION as the lead investor (with all of Aqua’s existing investors also participating in this round).

“We want to grow from a product perspective, we want to grow from a go-to-market [perspective] and expand our geographical coverage — and we also want to be a little more acquisitive. That’s another direction we’re looking at because now we have the platform that allows us to do that. […] I feel we can take the company to great heights. That’s the plan. The market opportunity allows us to dream big.”

 

Mar
09
2021
--

YL Ventures sells its stake in cybersecurity unicorn Axonius for $270M

YL Ventures, the Israel-focused cybersecurity seed fund, today announced that it has sold its stake in cybersecurity asset management startup Axonius, which only a week ago announced a $100 million Series D funding round that now values it at around $1.2 billion.

ICONIQ Growth, Alkeon Capital Management, DTCP and Harmony Partners acquired YL Venture’s stake for $270 million. This marks YL’s first return from its third $75 million fund, which it raised in 2017, and the largest return in the firm’s history.

With this sale, the company’s third fund still has six portfolio companies remaining. It closed its fourth fund with $120 million in committed capital in the middle of 2019.

Unlike YL, which focuses on early-stage companies — though it also tends to participate in some later-stage rounds — the investors that are buying its stake specialize in later-stage companies that are often on an IPO path. ICONIQ Growth has invested in the likes of Adyen, CrowdStrike, Datadog and Zoom, for example, and has also regularly partnered with YL Ventures on its later-stage investments.

“The transition from early-stage to late-stage investors just makes sense as we drive toward IPO, and it allows each investor to focus on what they do best,” said Dean Sysman, co-founder and CEO of Axonius. “We appreciate the guidance and support the YL Ventures team has provided during the early stages of our company and we congratulate them on this successful journey.”

To put this sale into perspective for the Silicon Valley and Tel Aviv-based YL Ventures, it’s worth noting that it currently manages about $300 million. Its current portfolio includes the likes of Orca Security, Hunters and Cycode. This sale is a huge win for the firm.

Its most headline-grabbing exit so far was Twistlock, which was acquired by Palo Alto Networks for $410 million in 2019, but it has also seen exits of its portfolio companies to Microsoft, Proofpoint, CA Technologies and Walmart, among others. The fund participated in Axonius’ $4 million seed round in 2017 up to its $58 million Series C round a year ago.

It seems like YL Ventures is taking a very pragmatic approach here. It doesn’t specialize in late-stage firms — and until recently, Israeli startups always tended to sell long before they got to a late-stage round anyway. And it can generate a nice — and guaranteed — return for its own investors, too.

“This exit netted $270 million in cash directly to our third fund, which had $75 million total in capital commitments, and this fund still has six outstanding portfolio companies remaining,” Yoav Leitersdorf, YL Ventures’ founder and managing partner, told me. “Returning multiple times that fund now with a single exit, with the rest of the portfolio companies still there for the upside is the most responsible — yet highly profitable path — we could have taken for our fund at this time. And all this while diverting our energies and means more towards our seed-stage companies (where our help is more impactful), and at the same time supporting Axonius by enabling it to bring aboard such excellent late-stage investors as ICONIQ and Alkeon — a true win-win-win situation for everyone involved!”

He also noted that this sale achieved a top-decile return for the firm’s limited partners and allows it to focus its resources and attention toward the younger companies in its portfolio.

Feb
17
2021
--

Spectral raises $6.2M for its DevSecOps service

Tel Aviv-based Spectral is bringing its new DevSecOps code scanner out of stealth today and announcing a $6.2 million funding round. The startup’s programming language-agnostic service aims to automated code security development teams to help them detect potential security issues in their codebases and logs, for example. Those issues could be hardcoded API keys and other credentials, but also security misconfiguration and shadow IT assets.

The four-person founding team has a deep background in building AI, monitoring and security tools. CEO Dotan Nahum was a Chief Architect at Klarna and Conduit (now Como, though you may remember Conduit from its infamous toolbar that was later spun off), and the CTO at Como and HiredScore, for example. Other founders worked on building monitoring tools at Elastic and HP and on security at Akamai. As Nahum told me, the idea for Spectral came to him and co-founder and COO Idan Didi during their shared time at mobile application build Conduit/Como.

Image Credits: Spectral

“We basically stored certificates for every client that we had, so we could submit their apps to the various marketplaces,” Nahum told me of his experience at Counduit/Como. “That certificate really proves that you are who you are and it’s super sensitive. And at each point at these companies, I really didn’t have the right tools to actually make sure that we’re storing, handling, detecting [this information] and making sure that it doesn’t leak anywhere.”

Nahum decided to quit his current job and started to build a prototype to see if he could build a tool that could solve this problem (and his work on this prototype quickly discovered an issue at Slack). And as enterprises move from on-premises software to the cloud and to microservices and DevOps, the need for better DevSecOps tools is only increasing.

“The emphasis is to create a great developer experience,” Nahum noted. “Because that’s where we started from. We didn’t start as a top down cyber tool. We started as a modest DevOps friendly, developer-friendly tool.”

Image Credits: Spectral

One interesting aspect of Spectral’s approach, which uses a machine learning model to detect these breaches across programming languages, is that it also scans public-facing systems. On the backend, Spectral integrates with tools like Travis, Jenkins, CircleCI, Webpack, Gatsby and Netlify, but it can also monitor Slack, npm, maven and log providers — tools that most companies don’t really think about when they think about threat modeling.

“Our solution prevents security breaches on a daily basis,” said Spectral co-founder and COO Idan Didi. “The pain points we’re addressing resonate strongly across every company developing software, because as they evolve from own-code to glue-code to no-code approaches they allow their developers to gain more speed, but they also add on significant amounts of risk. Spectral lets developers be more productive while keeping the company secure.”

The company was founded in mid-2020, but it already has about 15 employees and counts a number of large publicly-listed companies among its customers.

Jan
26
2021
--

Run:AI raises $30M Series B for its AI compute platform

Run:AI, a Tel Aviv-based company that helps businesses orchestrate and optimize their AI compute infrastructure, today announced that it has raised a $30 million Series B round. The new round was led by Insight Partners, with participation from existing investors TLV Partners and S Capital. This brings the company’s total funding to date to $43 million.

At the core of Run:AI’s platform is the ability to effectively virtualize and orchestrate AI workloads on top of its Kubernetes-based scheduler. Traditionally, it was always hard to virtualize GPUs, so even as demand for training AI models has increased, a lot of the physical GPUs often set idle for long periods because it was hard to dynamically allocate them between projects.

Image Credits: Run.AI

The promise behind Run:AI’s platform is that it allows its users to abstract away all of the AI infrastructure and pool all of their GPU resources — no matter whether in the cloud or on-premises. This also makes it easier for businesses to share these resources between users and teams. In the process, IT teams also get better insights into how their compute resources are being used.

“Every enterprise is either already rearchitecting themselves to be built around learning systems powered by AI, or they should be,” said Lonne Jaffe, managing director at Insight Partners and now a board member at Run:AI.” Just as virtualization and then container technology transformed CPU-based workloads over the last decades, Run:AI is bringing orchestration and virtualization technology to AI chipsets such as GPUs, dramatically accelerating both AI training and inference. The system also future-proofs deep learning workloads, allowing them to inherit the power of the latest hardware with less rework. In Run:AI, we’ve found disruptive technology, an experienced team and a SaaS-based market strategy that will help enterprises deploy the AI they’ll need to stay competitive.”

Run:AI says that it is currently working with customers in a wide variety of industries, including automotive, finance, defense, manufacturing and healthcare. These customers, the company says, are seeing their GPU utilization increase from 25 to 75% on average.

“The new funds enable Run:AI to grow the company in two important areas: first, to triple the size of our development team this year,” the company’s CEO Omri Geller told me. “We have an aggressive roadmap for building out the truly innovative parts of our product vision — particularly around virtualizing AI workloads — a bigger team will help speed up development in this area. Second, a round this size enables us to quickly expand sales and marketing to additional industries and markets.”

Oct
28
2020
--

Enso Security raises $6M for its application security posture management platform

Enso Security, a Tel Aviv-based startup that is building a new application security posture management platform, today announced that it has raised a $6 million seed funding round led by YL Ventures, with participation from Jump Capital. Angel investors in this round include HackerOne co-founder and CTO Alex Rice; Sounil Yu, the former chief security scientist at Bank of America; Omkhar Arasaratnam, the former head of Data Protection Technology at JPMorgan Chase and toDay Ventures.

The company was founded by Roy Erlich (CEO), Chen Gour Arie (CPO) and Barak Tawily (CTO). As is so often the case with Israeli security startups, the founding team includes former members of the Israeli Intelligence Corps, but also a lot of hands-on commercial experience. Erlich, for example, was previously the head of application security at Wix, while Gour Arie worked as an application security consultant for numerous companies across Europe and Tawily has a background in pentesting and led a security team at Wix, too.

Image Credits: Enso Security / Getty Images

“It’s no secret that, today, the diversity of R&D allows [companies] to rapidly introduce new applications and push changes to existing ones,” Erlich explained. “But this great complexity for application security teams results in significant AppSec management challenges. These challenges include the difficulty of tracking applications across environments, measuring risks, prioritizing tasks and enforcing uniform Application Security strategies across all applications.”

But as companies push out code faster than ever, the application security teams aren’t able to keep up — and may not even know about every application being developed internally. The team argues that application security today is often a manual effort to identify owners and measure risk, for example — and the resources for application security teams are often limited, especially when compared the size of the overall development team in most companies. Indeed, the Enso team argues that most AppSec teams today spend most of their time creating relationships with developers and performing operational and product-related tasks — and not on application security.

Image Credits: Enso Security / Getty Images

“It’s a losing fight from the application security side because you have no chance to cover everything,” Erlich noted. “Having said that, […] it’s all about managing the risk. You need to make sure that you take data-driven decisions and that you have all the data that you need in one place.”

Enso Security then wants to give these teams a platform that gives them a single pane of glass to discover applications, identify owners, detect changes and capture their security posture. From there, teams can then prioritize and track their tasks and get real-time feedback on what is happening across their tools. The company’s tools currently pull in data from a wide variety of tools, including the likes of JIRA, Jenkins, GitLab, GitHub, Splunk, ServiceNow and the Envoy edge and service proxy. But as the team argues, even getting data from just a few sources already provides benefits for Enso’s users.

Looking ahead, the team plans to continue improving its product and staff up from its small group of seven employees to about 20 in the next year.

“Roy, Chen and Barak have come up with a very elegant solution to a notoriously complex problem space,” said Ofer Schreiber, partner at YL Ventures . “Because they cut straight to visibility — the true heart of this issue — cybersecurity professionals can finally see and manage all of the applications in their environments. This will have an extraordinary impact on the rate of application rollout and enterprise productivity.”

Oct
14
2020
--

Dataloop raises $11M Series A round for its AI data management platform

Dataloop, a Tel Aviv-based startup that specializes in helping businesses manage the entire data life cycle for their AI projects, including helping them annotate their data sets, today announced that it has now raised a total of $16 million. This includes a $5 seed round that was previously unreported, as well as an $11 million Series A round that recently closed.

The Series A round was led by Amiti Ventures, with participation from F2 Venture Capital, crowdfunding platform OurCrowd, NextLeap Ventures and SeedIL Ventures.

“Many organizations continue to struggle with moving their AI and ML projects into production as a result of data labeling limitations and a lack of real-time validation that can only be achieved with human input into the system,” said Dataloop CEO Eran Shlomo. “With this investment, we are committed, along with our partners, to overcoming these roadblocks and providing next generation data management tools that will transform the AI industry and meet the rising demand for innovation in global markets.”

Image Credits: Dataloop

For the most part, Dataloop specializes in helping businesses manage and annotate their visual data. It’s agnostic to the vertical its customers are in, but we’re talking about anything from robotics and drones to retail and autonomous driving.

The platform itself centers around the “humans in the loop” model that complements the automated systems, with the ability for humans to train and correct the model as needed. It combines the hosted annotation platform with a Python SDK and REST API for developers, as well as a serverless Functions-as-a-Service environment that runs on top of a Kubernetes cluster for automating dataflows.

Image Credits: Dataloop

The company was founded in 2017. It’ll use the new funding to grow its presence in the U.S. and European markets, something that’s pretty standard for Israeli startups, and build out its engineering team as well.

Sep
15
2020
--

Data virtualization service Varada raises $12M

Varada, a Tel Aviv-based startup that focuses on making it easier for businesses to query data across services, today announced that it has raised a $12 million Series A round led by Israeli early-stage fund MizMaa Ventures, with participation by Gefen Capital.

“If you look at the storage aspect for big data, there’s always innovation, but we can put a lot of data in one place,” Varada CEO and co-founder Eran Vanounou told me. “But translating data into insight? It’s so hard. It’s costly. It’s slow. It’s complicated.”

That’s a lesson he learned during his time as CTO of LivePerson, which he described as a classic big data company. And just like at LivePerson, where the team had to reinvent the wheel to solve its data problems, again and again, every company — and not just the large enterprises — now struggles with managing their data and getting insights out of it, Vanounou argued.

varada architecture diagram

Image Credits: Varada

The rest of the founding team, David Krakov, Roman Vainbrand and Tal Ben-Moshe, already had a lot of experience in dealing with these problems, too, with Ben-Moshe having served at the chief software architect of Dell EMC’s XtremIO flash array unit, for example. They built the system for indexing big data that’s at the core of Varada’s platform (with the open-source Presto SQL query engine being one of the other cornerstones).

Image Credits: Varada

Essentially, Varada embraces the idea of data lakes and enriches that with its indexing capabilities. And those indexing capabilities is where Varada’s smarts can be found. As Vanounou explained, the company is using a machine learning system to understand when users tend to run certain workloads, and then caches the data ahead of time, making the system far faster than its competitors.

“If you think about big organizations and think about the workloads and the queries, what happens during the morning time is different from evening time. What happened yesterday is not what happened today. What happened on a rainy day is not what happened on a shiny day. […] We listen to what’s going on and we optimize. We leverage the indexing technology. We index what is needed when it is needed.”

That helps speed up queries, but it also means less data has to be replicated, which also brings down the cost. As MizMaa’s Aaron Applbaum noted, since Varada is not a SaaS solution, the buyers still get all of the discounts from their cloud providers, too.

In addition, the system can allocate resources intelligently so that different users can tap into different amounts of bandwidth. You can tell it to give customers more bandwidth than your financial analysts, for example.

“Data is growing like crazy: in volume, in scale, in complexity, in who requires it and what the business intelligence uses are, what the API uses are,” Applbaum said when I asked him why he decided to invest. “And compute is getting slightly cheaper, but not really, and storage is getting cheaper. So if you can make the trade-off to store more stuff, and access things more intelligently, more quickly, more agile — that was the basis of our thesis, as long as you can do it without compromising performance.”

Varada, with its team of experienced executives, architects and engineers, ticked a lot of the company’s boxes in this regard, but he also noted that unlike some other Israeli startups, the team understood that it had to listen to customers and understand their needs, too.

“In Israel, you have a history — and it’s become less and less the case — but historically, there’s a joke that it’s ‘ready, fire, aim.’ You build a technology, you’ve got this beautiful thing and you’re like, ‘alright, we did it,’ but without listening to the needs of the customer,” he explained.

The Varada team is not afraid to compare itself to Snowflake, which at least at first glance seems to make similar promises. Vananou praised the company for opening up the data warehousing market and proving that people are willing to pay for good analytics. But he argues that Varada’s approach is fundamentally different.

“We embrace the data lake. So if you are Mr. Customer, your data is your data. We’re not going to take it, move it, copy it. This is your single source of truth,” he said. And in addition, the data can stay in the company’s virtual private cloud. He also argues that Varada isn’t so much focused on the business users but the technologists inside a company.

 

Aug
12
2020
--

Adaptive Shield raises $4M for its SaaS security platform

Adaptive Shield, a Tel Aviv-based security startup, is coming out of stealth today and announcing its $4 million seed round led by Vertex Ventures Israel. The company’s platform helps businesses protect their SaaS applications by regularly scanning their various setting for security issues.

The company’s co-founders met in the Israeli Defense Forces, where they were trained on cybersecurity, and then worked at a number of other security companies before starting their own venture. Adaptive Shield CEO Maor Bin, who previously led cloud research at Proofpoint, told me the team decided to look at SaaS security because they believe this is an urgent problem few other companies are addressing.

Pictured is a representative sample of nine apps being monitored by the Adaptive Shield platform, including the total score of each application, affected categories and affected security frameworks and standards. (Image Credits: Adaptive Shield)

“When you look at the problems that are out there — you want to solve something that is critical, that is urgent,” he said. “And what’s more critical than business applications? All the information is out there and every day, we see people moving their on-prem infrastructure into the cloud.”

Bin argues that as companies adopt a large variety of SaaS applications, all with their own security settings and user privileges, security teams are often either overwhelmed or simply not focused on these SaaS tools because they aren’t the system owners and may not even have access to them.

“Every enterprise today is heavily using SaaS services without addressing the associated and ever-changing security risks,” says Emanuel Timor, general partner at Vertex Ventures Israel . “We are impressed by the vision Adaptive Shield has to elegantly solve this complex problem and by the level of interest and fast adoption of its solution by customers.”

Onboarding is pretty easy, as Bin showed me, and typically involves setting up a user in the SaaS app and then logging into a given service through Adaptive Shield. Currently, the company supports most of the standard SaaS enterprise applications you would expect, including GitHub, Office 365, Salesforce, Slack, SuccessFactors and Zoom.

“I think that one of the most important differentiators for us is the amount of applications that we support,” Bin noted.

The company already has paying customers, including some Fortune 500 companies across a number of verticals, and it has already invested some of the new funding round, which closed before the global COVID-19 pandemic hit, into building out more integrations for these customers. Bin tells me that Adaptive Shield immediately started hiring once the round closed and is now also in the process of hiring its first employee in the U.S. to help with sales.

Jul
30
2020
--

Buildots raises $16M to bring computer vision to construction management

Buildots, a Tel Aviv and London-based startup that is using computer vision to modernize the construction management industry, today announced that it has raised $16 million in total funding. This includes a $3 million seed round that was previously unreported and a $13 million Series A round, both led by TLV Partners. Other investors include Innogy Ventures, Tidhar Construction Group, Ziv Aviram (co-founder of Mobileye & OrCam), Magma Ventures head Zvika Limon, serial entrepreneurs Benny Schnaider and  Avigdor Willenz, as well as Tidhar chairman Gil Geva.

The idea behind Buildots is pretty straightforward. The team is using hardhat-mounted 360-degree cameras to allow project managers at construction sites to get an overview of the state of a project and whether it remains on schedule. The company’s software creates a digital twin of the construction site, using the architectural plans and schedule as its basis, and then uses computer vision to compare what the plans say to the reality that its tools are seeing. With this, Buildots can immediately detect when there’s a power outlet missing in a room or whether there’s a sink that still needs to be installed in a kitchen, for example.

“Buildots have been able to solve a challenge that for many seemed unconquerable, delivering huge potential for changing the way we complete our projects,” said Tidhar’s Geva in a statement. “The combination of an ambitious vision, great team and strong execution abilities quickly led us from being a customer to joining as an investor to take part in their journey.”

The company was co-founded in 2018 by Roy Danon, Aviv Leibovici and Yakir Sundry. Like so many Israeli startups, the founders met during their time in the Israeli Defense Forces, where they graduated from the Talpiot unit.

“At some point, like many of our friends, we had the urge to do something together — to build a company, to start something from scratch,” said Danon, the company’s CEO. “For us, we like getting our hands dirty. We saw most of our friends going into the most standard industries like cloud and cyber and storage and things that obviously people like us feel more comfortable in, but for some reason we had like a bug that said, ‘we want to do something that is a bit harder, that has a bigger impact on the world.’ ”

So the team started looking into how it could bring technology to traditional industries like agriculture, finance and medicine, but then settled upon construction thanks to a chance meeting with a construction company. For the first six months, the team mostly did research in both Israel and London to understand where it could provide value.

Danon argues that the construction industry is essentially a manufacturing industry, but with very outdated control and process management systems that still often relies on Excel to track progress.

Image Credits: Buildots

Construction sites obviously pose their own problems. There’s often no Wi-Fi, for example, so contractors generally still have to upload their videos manually to Buildots’ servers. They are also three dimensional, so the team had to develop systems to understand on what floor a video was taken, for example, and for large indoor spaces, GPS won’t work either.

The teams tells me that before the COVID-19 lockdowns, it was mostly focused on Israel and the U.K., but the pandemic actually accelerated its push into other geographies. It just started work on a large project in Poland and is scheduled to work on another one in Japan next month.

Because the construction industry is very project-driven, sales often start with getting one project manager on board. That project manager also usually owns the budget for the project, so they can often also sign the check, Danon noted. And once that works out, then the general contractor often wants to talk to the company about a larger enterprise deal.

As for the funding, the company’s Series A round came together just before the lockdowns started. The company managed to bring together an interesting mix of investors from both the construction and technology industries.

Now, the plan is to scale the company, which currently has 35 employees, and figure out even more ways to use the data the service collects and make it useful for its users. “We have a long journey to turn all the data we have into supporting all the workflows on a construction site,” said Danon. “There are so many more things to do and so many more roles to support.”

Image Credits: Buildots

Powered by WordPress | Theme: Aeros 2.0 by TheBuckmaker.com