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Locus Robotics raises $40 million to take its warehouse robots global

June 2, 2020 Big Data

Warehouse robotics startup Locus Robotics today announced it has raised $ 40 million, the bulk of which will be put toward accelerating R&D and the company’s expansion into new markets, including in the EU, where it opened a new headquarters. CEO Rich Faulk says Locus also intends to launch strategic reseller partnerships throughout 2020, following a year in which its number of customer deployments passed 50.

Worker shortages attributable to the pandemic have accelerated the adoption of automation. According to ABI Research, more than 4 million commercial robots will be installed in over 50,000 warehouses around the world by 2025, up from under 4,000 warehouses as of 2018. In China, Oxford Economics anticipates 12.5 million manufacturing jobs will become automated, while in the U.S., McKinsey projects machines will take upwards of 30% of such jobs.

Locus’ autonomous robots — LocusBots — can be reconfigured with virtually any tote, box, bin, or container or with peripherals like barcode scanners, label printers, and environmental sensors designed to expedite order processing. They work collaboratively with human associates, minimizing walking with a UI that recognizes workers’ Bluetooth badges and switches to their preferred language. On the backend, Locus’ LocusServer orchestrates multiple robots such that they learn efficient travel routes, sharing the information with other robots and clustering orders to where workers are. As orders come into warehouse management systems, Locus organizes them before transmitting back confirmations — providing managers real-time performance data, including productivity, robot status, and more.

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When new LocusBots are added to the fleet, they share warehouse inventory status and item locations. Through LocusServer, they detect blockages and other traffic issues to improve item pick rates and order throughput. Locus’ directed picking technology actively directs workers to their next pick location, letting them select their own pace while optionally accepting challenges through a gamification feature that supports individual, team, and shift goals plus events and a mechanism managers can use to provide feedback. In addition, Locus’ backend collates various long-tail metrics, including hourly pick data, daily and monthly pick volume, current robot locations, and robot charging levels.

Locus offers a “robot-as-a-service” program through which customers can scale up by adding robots on a limited-time basis. For a monthly subscription fee, the company sends or receives robots to warehouses upon request, and it provides those robots software and hardware updates, in addition to maintenance.

Locus claims that its system — which takes about four weeks to deploy — has delivered a 2 to 3 times increase in productivity and throughput and 15% less overtime spend for brands that include Boots UK, Verst Logistics, Ceva, DHL, Material Bank, Radial, Port Logistics Group, Marleylilly, and Geodis. The company’s robots passed 100 million units picked in February, and in April, UPS announced that it would be piloting Locus machines in its own facilities.

“COVID-19 has dramatically accelerated trends that have been taking shape over several years in the logistics market, including the movement to collaborative robotics to deal with the labor crisis,” Faulk told VentureBeat via email, adding that the company’s annual recurring revenue increased 300% in 2020 year-over-year. “Our pipeline is expanding weekly with major global brands needing to automate prior to peak season to address the labor gap they will face this year.”

Zebra Technologies’ Zebra Ventures led this series D investment in Wilmington, Massachusetts-based Locus, with participation from existing backers, including Scale Venture Partners. This round brings the Quiet Logistics spinout’s total raised to over $ 105 million as it looks to expand its workforce from more than 120 people to 200 by 2021.

Locus competes in the $ 3.1 billion intelligent machines market with Los Angeles-based robotics startup InVia, which leases automated robotics technologies to fulfillment centers. Gideon Brothers, a Croatia-based industrial startup backed by TransferWise cofounder Taavet Hinrikus, is another contender. And then there’s robotics systems company GreyOrange; Otto Motors; and Berkshire Grey, which combines AI and robotics to automate multichannel fulfillment for retailers, ecommerce, and logistics enterprises. Fulfillment alone is a $ 9 billion industry — roughly 60,000 employees handle orders in the U.S., and companies like Apple manufacturing partner Foxconn have deployed tens of thousands of assistive robots in assembly plants overseas.

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Evervault raises $16 million for ‘privacy cages’ that simplify data protection

May 21, 2020 Big Data

Evervault has raised $ 16 million in venture capital to develop technology the Dublin-based company claims will recalibrate the traditional tradeoffs between privacy and regulation. Index Ventures led the round, which includes previous investors Sequoia Capital, Kleiner Perkins, and Frontline Ventures. In addition, the fundraising attracted money from a string of notable angel investors, such as Eventbrite cofounder Kevin Hartz and former Facebook chief security officer Alex Stamos.

The funding is notable because Evervault has not yet developed a product that’s ready for customers. Instead, investors are betting on a concept that promises to effectively eliminate the need for privacy regulations, a shift that would save businesses considerable expenses on compliance while delivering greater data protection for consumers.

“Data privacy is very complicated for people who don’t want to read thousands of pages of regulations,” said Evervault founder and CEO Shane Curran. “I started Evervault with the belief that data privacy is a technology problem rather than a regulatory problem.”

In Europe, the advent of Europe’s General Data Protection Regulation (GDPR) in May 2018 has sparked a wave of startups promising to help businesses comply with the rules. Curran said he first began working on the problem in high school and officially started the company in 2018.

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He began by establishing a privacy manifesto that lays out eight rules any such system should follow. Primary among these is the idea that “data should always be caged.” That means any sensitive data leaving your device should be encrypted so that it can only be treated and processed in a “privacy cage.”

Curran described these cages as containers that allow for fully encrypted data to be processed so that only the owner of the original data can access the resulting information. The company processing the data would be excluded from accessing it directly and would really only have momentary possession of a user’s data to perform a promised service. Once that service is completed, the data would essentially vanish from the company’s system.

“Containers let you run computing over really sensitive data,” Curran said. “Companies can manage without them having to sacrifice privacy or security.”

Evervault plans to offer this service as an API, with the aim of allowing developers to seamlessly build it into the software stack of whatever they are creating. Curran likes to say that developers will be able to do more with one line of code than the entire set of GDPR regulations.

This would theoretically speed product development while also lifting the burden on companies who might otherwise spend huge resources ensuring they are complying with privacy regulations. Likewise, it would help regulators whose enforcement resources are stretched thin, Curran said.

Still, the investors are taking a leap of faith here. But Evervault’s eight employees are hard at work developing the technology and are currently working alongside partners in sectors with sensitive data issues, like finance.

Curran said he doesn’t have a firm timeline for an initial public release yet. “The roadmap is what I think they really bought into,” Curran said. “That, and the team.”

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Dathena raises $12 million for AI that monitors and classifies sensitive enterprise data

May 14, 2020 Big Data

Dathena, a startup employing AI and machine learning to identify and protect sensitive enterprise data, today announced that it secured $ 12 million in equity financing. The fresh capital follows the opening of the company’s U.S. headquarters in New York City, and CEO Christopher Muffat says the funding will support Dathena’s R&D efforts and the hiring of stateside staff across sales, marking, and customer success teams.

Dathena’s platform is designed to help companies protect against breaches while remaining in compliance with GDPR, the California Consumer Privacy Act (CCPA), and other such regulations. About 37% of businesses operating in the EU say they’ve had to hire at least six new employees to achieve GDPR compliance (according to Netsparker), and among those that have experienced a data breach, the average cost amounted to $ 3.6 million or $ 141 for each record lost (according to the Ponemon Institute).

Five products form Darthena’s suite: Discovery, Privacy, Classify, Protect, and Detect.

Discovery and Privacy reveal what kind of files are stored throughout an organization, where they’re located, and who has access to them at any one time. In addition, they identify business-critical data, sort by toxicity and risk, and eliminate duplicates while mapping all personally identifiable data into a comprehensive backend library.

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Classify filters data by business category and level of confidentiality, automatically labeling sensitive information and delivering visualizations of files to managers and administrators. It learns organizations’ documentation patterns for data in motion and at rest, achieving 80% accuracy out of the box and up to 99% after deployment, Darthena claims.

As for Protect and Detect, they ensure classification tags and keywords export to third-party information security systems and shed light on who, how, when, and where employees are creating and accessing data. Detect provides continuous monitoring and spotlighting of data access and storage anomalies, for its part, as well as smart alerts and integrated workflows for IT team remediation.

Dathena competes with well-funded startups like OneTrust and Bitglass in the $ 120 billion data protection market, but it claims to have over 200,000 users and “a multitude” of enterprise clients. Muffat expects to see an uptick in inquiries in the coming months as remote work motivated by the pandemic gives rise to data protection challenges.

Jungle Ventures led this latest funding round (a series A), with participation from Caphorn and Enterprise Singapore’s SEEDS Capital and existing investors Cerracap Ventures and MS&AD Ventures. It follows a previously undisclosed seed round in November 2018.

Muffat, who worked with HSBC as a lead investigator and headed information risk management at Barclays, founded Dathena in 2016. More than 100 employees work out of its headquarters in Singapore and offices in Geneva.

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FarEye raises $25 million to orchestrate deliveries with AI

April 15, 2020 Big Data

FarEye, a startup developing a predictive transportation logistics platform, today announced that it raised $ 25 million in equity financing. The new tranche comes as global supply chains become strained by demand related to COVID-19; earlier this week, to combat overcapacity, Amazon imposed a cap on grocery delivery and pickup customers.

It’s FarEye’s assertion that its software-as-a-service (SaaS) solution can anticipate and respond to influxes in demand in real time, improving the purchasing and selling experience. The company claims to eliminate 55% of risks like theft and pilferage and to reduce delivery turnaround, loading, transit, and unloading time by 25% to 32%.

FarEye’s Java-based, Microsoft Azure-backed Serve platform enables the company’s over 150 clients — among them Domino’s, Walmart, Amway, 7-Eleven, and DHL — to orchestrate and track logistics operations with automatic dispatching and order allocation, electronic proof of delivery, customer-facing apps, and other such tools. Serve anticipates delays and handles exceptions, while at the same time optimizing delivery routes to reduce miles per delivery and boost fleet productivity, taking into account things like traffic, weather, and detours. Machine learning algorithms use data from past pickup and delivery attempts to improve future estimates, and over a billion customers’ addresses are geocoded to boost successful first-attempt delivery rates.

Additionally, Serve provides delivery progress reports and a drag-and-drop, single-touch interface that lets managers update customer preferences on the fly, alongside an AI-powered chat platform that plugs into existing systems to expedite customer inquiry resolutions. According to CEO Kushal Nahata, the platform handles over 10 million transactions per day for couriers, retailers, manufacturers, grocers, and others.

To aid more directly in the fight against COVID-19, FarEye recently began offering select products at no charge until June 2020 to customers handling daily essential item deliveries. Hospital sites and non-governmental organizations can access those same tools for free until September.

This latest investment in Noida, India-based FarEye (a series D) was led by M12, Microsoft’s corporate venture fund, with participation from Eight Roads Ventures, Honeywell Ventures, and existing investor SAIF Partners. It brings the total venture capital raised by the company, which has over 350 employees (and plans to grow that workforce to 500 by 2021), to nearly $ 60 million following an approximately $ 7.9 million series C in February 2018.

FarEye competes with startups like SourceDay and Flock Freight in the global logistics space, which is anticipated to be worth $ 15.5 trillion by 2023. Uber offers a service called Uber Freight, to which it recently committed another $ 200 million as part of a major expansion. San Francisco-based startup KeepTruckin last year secured $ 149 million to further develop its shipment marketplace, and Next Trucking closed a $ 97 million investment. For its part, Convoy raised $ 400 million at a $ 2.75 billion valuation to make freight trucking more efficient.

But FarEye has an advantage in that it has been profitable “since day one,” according to Nahata — it makes money by charging a license fee and transaction fees, as well as for vertical-specific services. He said the company “will use this investment to create greater value and improve the experience for our customers by enhancing the platform’s predictive capabilities, increasing platform partnerships, expanding into new markets and growing our teams” in Europe, Asia, and the U.S.

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Diligent Robotics raises $10 million for nurse assistant robot Moxi

March 22, 2020 Big Data

Diligent Robotics today announced the close of a $ 10 million round to expand its fleet of nurse assistant robots for hospitals. The round was led by DNX Ventures, with participation from True Ventures, Ubiquity Ventures, Next Coast Ventures, Grit Ventures, E14 Fund, and Promus Ventures.

Moxi is designed to reduce nurse workloads by handling tasks like collecting supplies, gathering soiled linens, and delivering fresh ones, and it’s coming to market during the COVID-19 crisis, when nurses are in short supply. In addition to tackling mundane aspects of the job, the robot can also help reduce health care professionals’ exposure to disease.

Moxi was created by Diligent Robotics at University of Texas, Austin by CEO Dr. Andrea Thomaz, a roboticist and professor who previously ran the Georgia Tech Socially Intelligent Machines Lab.

“It’s a really good time to be working on this problem,” Thomaz told VentureBeat in a phone interview. “Now more than ever there’s kind of a spotlight on how overworked [nurses are] and what a shortage there is of frontline hospital staff, so we’re anxious to get more robots out there to help.”

Robots like UVD’s ultraviolet light-emitting robot and others used for telepresence are being deployed to fight COVID-19.

Moxi underwent over 3,000 hours of testing in Austin and Dallas, Texas hospitals in 2018 and 2019, and earlier this year the robot was placed with its first customer, Medical City Healthcare in Dallas. Diligent Robotics has not yet shared specific data on just how much time Moxi saves human nurses, but those figures may be shared in a future whitepaper, Thomaz said.

Diligent Robotics previously raised $ 5 million in a seed round. The company was founded in 2017, has 18 employees, and is based in Austin.

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Vida Diagnostics raises $11 million to diagnose lung diseases with AI

March 12, 2020 Big Data

Vida Diagnostics, a provider of AI-powered lung imaging analysis tools, today announced that it’s raised $ 11 million. CEO Susan A. Woods said the funds will be used to accelerate the commercialization and expansion of the company’s product portfolio, which she says could address market deficits in the early assessment, monitoring, and treatment of lung disease.

“We are driven to continuously raise the standard of care for patients with or at risk of lung disease. By equipping care teams with LungPrint, patient care and quality of life can be positively affected,” said Wood, who noted that lung disease impacts over 500 million people globally. “Vida is endlessly thankful for the extensive support of the people, resources, and programs from the State of Iowa leading to this expansive funding. Vida can now accelerate LungPrint’s market access, further connecting its benefits to the many millions of patients with lung disease.”

Vida’s LungPrint uses medical data including chest CT scans to provide a set of insights that could help to inform treatment options. It integrates with radiology workflows, automatically quantitating lung density that may be indicative of emphysema and interstitial lung abnormalities, while providing planning and guidance for conditions like bronchoscopists, interventional pulmonologists, and thoracic surgeons. Using special topographic MPR techniques that sample and project non-overlapping airways onto a single image, Vida claims that LungPrint is able to preserve CT scan resolution as well as the context of the surrounding tissue.

Beyond LungPrint — which Vida says is FDA cleared, CE-marked, Health Canada licensed and TGA registered for clinical use in the U.S., European Economic Area, Canada, and Australia — the company supports clinical trials with a range of services. Among them are pre-clinical imaging consulting; imaging protocol and imaging charter development; site qualification and training; data collection, storage, and management; quantitative CT assessment of lung function; expert, blinded image review project management and quality assurance; data analysis and interpretation.

“Pulmonology and radiology are severely underserved areas of healthcare – the need is expanding and the number of clinicians is limited. VIDA is in an optimal position to deliver innovation and increase access,” said First Analysis managing director and general partner Tracy Marshbanks in a statement. “This investment will enable Vida to meet the growing call for precise AI-driven lung analysis solutions that can help improve the quality of diagnosis and life for patients impacted by lung disease.”

Vida is one of several startups applying AI to health care challenges. Paige recently raised $ 45 million to continue its work in cancer diagnosis with AI models trained using clinical imaging data, and Aidoc nabbed $ 27 million for AI-assisted head, chest, abdominal, and spinal exams. Healthy.io taps machine learning to conduct urinalysis. Sight Diagnostics — which has raked in over $ 27.8 million in funding — leverages a family of algorithms to perform point-of-care complete blood count (CBC) tests with no more than a pinprick of blood. And just last month, Qure.ai snagged $ 16 million for AI that spots abnormalities in chest and head scans.

Coralville, Iowa-based Vida’s latest funding round was a series C, and it was led by Analysis Corporation with initial equity participation from Blue Heron Capital, UnityPoint Health Ventures, Next Level Ventures, Chartline Capital Partners, Rural Vitality Fund, Rittenhouse Ventures, Iowa First Capital Fund, and The Angels’ Forum. It brings the company’s total raised to date to over $ 20 million.

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SiLC Technologies raises $12 million for long-range lidar sensors

March 4, 2020 Big Data

SiLC Technologies, a silicon photonics startup specializing in photonic sensor and 3D imaging applications, today announced that it has closed a $ 12 million seed financing round. Founder and CEO Mehdi Asghari says that it’ll allow the company to refine its 4D+ Vision Chip lidar sensor, which it claims exceeds the range, resolution, and accuracy of most lidar sensors on the market in a smaller footprint.

Those advantages — along with the velocity, light polarization, reflectivity, and other vectors that the 4D+ Vision Chip measures — could be a boon for startups developing autonomous cars, which require sensors to detect potential obstacles up to 200 meters away. “This is my third startup and by far the most exciting, both at a technology level and the size of market it can address,” said Asghari, who was part of the executive team that led fiber optics company Bookham Technologies to its initial public offering and who later joined the C-suite at Kotura, which was acquired by Mellanox in 2013. “We believe we have an opportunity to transform several industries. Our 4D+ Vision Chip technology will not only make lidar a commercial reality, but will also enable applications ranging from robotics to AR/VR to biometric scanning.”

SiLC’s single-chip optical engine incorporates both lasers and detector components, and it operates at the 1550nm wavelength — the same wavelength used by a prototype demoed by lidar startup Luminar in July 2017. (Asghari says this makes it highly energy-efficient and robust against interference from other lidar sensors and sunlight.) The fully integrated, frequency-modulated continuous wave sensor taps second-generation silicon photonics to scan its surroundings, enabling it to detect objects smaller than one-and-a-half inches at a range of 200 meters (which translates to a resolution of about 0.01 degrees vertically and horizontally).

In a test at CES 2020, a 4D+ Vision Chip unit detected a rooftop security camera post from 190 meters away and a lamp post from 250 meters away. SiLC claims that in optimal conditions, its maximum range is around 300 meters.

“Integrating all essential functions necessary to build a … chip on a cost-effective silicon platform represents the holy grail of lidar,” said Dell Technologies Capital managing director Daniel Docter, an investor. “SiLC’s team has over 20 years of experience and a proven track record commercializing silicon photonics solutions. After looking at more than 30 different lidar companies, we found SiLC to be the only company that has a viable approach for large-scale adoption of lidar in automotive and industrial robotics.”

SiLC is headquartered in Monrovia, California. In addition to Dell, which led the round, Decent Capital, ITIC Ventures, and undisclosed angel investors participated in the funding round.

The lidar market is projected to be worth $ 1.8 billion in just five years, and it’s a crowded field, to say the least. Innoviz raised $ 38 million in June, following financing tranches by Oryx and TetraVue. Lidar startup Baraja last January raised $ 32 million for its innovative prism-like optics design, and Alphabet subsidiary Waymo said last year that it would begin selling its proprietary near-range, 360-degree lidar design — Laser Bear Honeycomb — to “dozens” of customers. That’s not to mention far-infrared pioneer AdaSky, ground-penetrating radar startup WaveSense, and velocity-measuring sensor company Aeva, all three of which seek to develop technologies that complement traditional vision-based autonomous car perception systems.

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Big Data – VentureBeat

Lendio raises $55 million to surface small business loans using machine learning

March 2, 2020 Big Data

Lendio, a company that provides a platform that taps algorithms to match customers with lenders and secure loans, announced that it raised $ 55 million. CEO Brock Blake says the influx of funds will bolster Lendio’s marketplace while enabling it to introduce new bookkeeping and lender services functions.

Lendio claims to make it easier for small- and medium-sized business owners to secure loans. Using machine learning, it can streamline the whole process, which usually includes comparing lenders and juggling things like credit scores, collateral, and fees

“This … round is a significant milestone in Lendio’s mission to fuel the American dream as a financial matchmaker that brings high-tech, high-touch capital to the small business economy,” added Blake, who cofounded the South Jordon, Utah-based company in 2011 with Levi King and Trent Miskin. “With these funds, we are strongly positioned to grow our existing platform as a trusted loan facilitator that supports both lenders and borrowers, while building out a range of new integrated lending services that get the right loans into the right hands at the right time.”

On Lendio’s website, businesses fill out a fee- and obligation-free application that takes about 15 minutes and doesn’t impact their credit score. Then, they’re able to explore business line of credit, small business loan, short-term loan, business-term loan, merchant cash advance, business credit card, equipment financing, commercial mortgage, accounts receivable financing, startup loan, and business acquisition offers from over 75 partners including American Express, Chase, PayPal, LendingClub, Kabbage, Comcast Business, Staples, and Funding Circle.

The machine learning algorithms underpinning Lendio’s marketplace take into account factors like offer likelihood (i.e., whether the lender will give the applicant an offer), funding likelihood (whether the applicant is likely to accept an offer), and the applicant’s product market. According to Brock, they’re trained on over 140 dimensions about the borrowers and their business and more than 800,000 possible deals, enabling Lendio to find financing for more than 65% of applicants compared with the 20% who successfully obtain bank loans. “This helps capture the ideal balance between the lender’s funding target and what works well for the borrower, and deep integrations with lenders allow for programmatic and instant submissions,” he told VentureBeat via email.

Lendio says it’s funded $ 1.4 billion in capital across 73,000 loans, which the company asserts makes its marketplace the largest of its kind in the U.S. Over the past two years, year-over-year growth averaged 75%, and the number of loans facilitated grew to over 100,000 (totaling $ 2 billion),

Brock says the financing from this latest round will also be used to grow Lendio’s Sunrise product, a money management dashboard that helps customers visualize their cash flow and finances. It supports customized invoices and lets users link both bank accounts and credit cards, and it ships with templates for profit and loss, balance sheet, tax summary, customer statement, and accounts receivable reports. Business owners can invite accountants to access transactions and financial reports, who can add sales tax to invoices based on customers’ locations, and they benefit from backups across multiple data centers over encrypted connections.

Additionally, Lendio plans to enhance its lender services division, which provides banks, credit unions, and online lenders access to a custom, white-labeled online app that lets them accept loan applications online.

About $ 31 million of Lendio’s latest raise was equity, led by Mercato Partners’ Traverse Fund, while $ 24 million was a debt facility from Signature Bank. The company has raised over $ 100 million in venture capital to date, and it employs over 300 people according to LinkedIn data.

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Nerdio raises $8 million to help businesses manage Microsoft Azure deployments

February 11, 2020 Big Data

Managing a cloud environment takes time, capital, and plenty in the way of domain expertise. This reality is the driving force behind a category of startups developing tools to automate the deployment and orchestration work — the managed services market was valued at around $ 186 billion in 2019, with forecasts suggesting that it could grow to $ 356.24 billion by 2025.

One contender in the space is Nerdio, which offers a product for managed service providers to build and grow their cloud practices in Microsoft’s Azure. This morning, the Chicago, Illinois-based company announced that it has closed an $ 8 million series A round led by MK Capital, with participation from Nerdio’s own cofounder and CEO, Vadim Vladimirskiy, and chief revenue officer, Joseph Landes. The infusion brings Nerdio’s total raised to over $ 10 million, following a $ 2.4 million round in February 2014. Vladimirskiy says it’ll be used to further develop existing products while expanding operations and supporting partners.

“Public cloud adoption is on the rise. It’s not slowing down anytime soon, and neither are we,” said Vladimirskiy in a statement. “We have evolved alongside the cloud industry — starting out as a [managed service provider], offering a private cloud business, and now being all-in on Azure. Nothing illustrates our commitment to the cloud, Microsoft, and our growing impact on both more than this financial commitment to propel Nerdio’s path forward.”

Nerdio is a subsidiary of Adar, which Vladimirskiy, Stuart Gabel, and Niall Keegan founded in 2005 to provide online backup systems to small and mid-sized enterprises. Soon after it was founded, Adar transitioned into managing virtual infrastructure, which is how Nerdio and its services came about.

Nerdio’s solutions suite for Azure lets admins automatically provision an IT environment and manage their clients from a single portal. A cost estimator prices out products and services prior to deployment, while an autoscaling algorithm ensures clients only pay for what they use. From an app for iOS and Android, credential users can access customer information and view server logs or perform tasks like editing and removing groups, configuring shared mailboxes, and stopping or starting remote servers. They’re also able to clone existing virtual machines to Azure and inventory environments for migration and automatically invoice customers for both resources used and services rendered.

Nerdio also offers the eponymous Nerdio Private Cloud, a service that delivers IT support and infrastructure, including virtual hardware, software, security backup and disaster recovery. It creates a virtual server infrastructure in a cloud-hosted environment — access to which is provided through Virtual Desktop Infrastructure (VDI) — and an image to standardize the virtual desktop environment, including all applications needed to access network resources. All of its software is collated and managed by Nerdio and its partners, including patches, upgrades, and compatibility tests.

“We have deep experience in the software and cloud infrastructure sectors and interact with plenty of emerging and innovative startups in ITaaS, IaaS and DaaS — few of which are as impactful and impressive as Nerdio and their Nerdio for Azure offerings,” said MK Capital’s Bret Maxwell. “Rarely do we have the chance to invest side by side with executive leaders like Vadim and Joseph who believe so strongly in their company’s mission and trajectory, which only strengthens our viewpoint that it is an incredibly exciting time to propel Nerdio’s growth forward.”

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Cherre raises $16 million to analyze real estate data with AI

February 5, 2020 Big Data

Real estate data collection and analytics costs can total in the millions of dollars. That’s why in 2016, L.D. Salmanson founded Cherre, a startup that leverages AI to cost-effectively resolve property data from disparate public and private sources. After raising $ 9 million in October 2018, the New York-based company today announced that it’s snagged $ 16 million in venture and debt funding led by Intel Capital, with participation from Navitas Capital, Carthona Capital, Zigg Capital, Dreamit Ventures, and Silicon Valley Bank.

“Last year was marked by incredible growth for the entire market,” said Salmanson, who noted that this latest capital infusion brings Cherre’s total raised to $ 25 million. “This massive industry migration towards fully integrated data systems is just starting, and we’re incredibly proud to be leading the charge. We look forward to continue working with our most demanding clients on their mission-critical data needs.”

Cherre’s technology is modeled after high-frequency trading platforms, and as such, it continuously organizes and updates internal and external databases. With the help of machine learning models that programmatically identify and index real estate data, it provides relevant info on demand in a clean and readable format.

Cherre’s software-as-a-service (SaaS) suite consists of several core components: CoreConnect, CoreAugment, CoreExplore, and CorePredict. The first three fall under the category of data management — they integrate with new and existing on-premises and cloud stores to provide location, transportation, social, and demographic information via APIs, which get compiled into dashboard visualizations. Explore has thousands of filters including custom queries, which support programmatic overlays and help to identify property owners behind corporations.

As for CorePredict, it taps AI supervised by asset managers and underwriters to source and evaluate new opportunities. In addition to automated asset evaluation and recommendation, the tool handles automated risk analysis and mitigation, as well as return on investment modeling and real-time forecasting.

Cherre has one of the largest real estate knowledge graphs in the world, according to Salmanson, with over 315 unique data sets and two billion data points pertaining to 177 million properties and 84 million companies. Its predictive models take into account property characteristics like amenities, materials, and zoning; community and demographics such as population, languages, and schools; recorder and deed transaction information; lien and mortgages; geospatial information; boundaries; tax and assessment; and valuations derived from over 450 million transactions across 100 million properties.

“The global real estate industry is undergoing a transformation, catalyzed by massive data flows and the application of artificial intelligence. Despite its substantial impact on the global economy, this sector is still in its infancy when it comes to data-centric investing and underwriting decisions,” said Intel Capital vice president Trina Van Pelt. “We see Cherre as critical infrastructure to accelerate the future of this industry. Our customer diligence repeatedly indicated Cherre’s AI-enabled platform was a foundational pillar — a data system of record for large enterprises across the real estate segment. We’re excited to help accelerate Cherre’s global growth trajectory.”

Cherre might not be the first in the $ 8.5 trillion real estate market with sophisticated AI-powered analytics tools — properties startup Compass recently raised $ 400 million for its big data platform, following hot on the heels of Skyline‘s $ 18 million round and other raises by HomeLight, Reonomy, and Geophy. But it has managed to attract a few notable Fortune 500 clients, including The Real Estate Board of NY (REBNY), Keller Williams NYC, Stratus Data Systems, August Partners, and Platinum Properties.

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Big Data – VentureBeat

Tag Archives: raises

Locus Robotics raises $40 million to take its warehouse robots global

Evervault raises $16 million for ‘privacy cages’ that simplify data protection

Dathena raises $12 million for AI that monitors and classifies sensitive enterprise data

FarEye raises $25 million to orchestrate deliveries with AI

Diligent Robotics raises $10 million for nurse assistant robot Moxi

Vida Diagnostics raises $11 million to diagnose lung diseases with AI

SiLC Technologies raises $12 million for long-range lidar sensors

Lendio raises $55 million to surface small business loans using machine learning

Nerdio raises $8 million to help businesses manage Microsoft Azure deployments

Cherre raises $16 million to analyze real estate data with AI

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