Robotic technology will shape the world for better efficiency.

The Robotic Industry is changing the landscape of work in the modern era. Right from automation in every industry to autonomous surgeries in healthcare, robotics is now becoming capable of handling intricate responsibilities and repetitive tasks and perform them without errors. This is one of the reasons, industries are increasing their dependency on robotics. While this indicates the future of the industry, many organizations and startups are leveraging this demand to create innovative solutions.

Here are the robotic companies that received funding in the month of July to carry on their work and research.

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1. Realtime Robotics

Realtime Robotics is an autonomous industrial robotics company. The company offers real-time, collision-free motion planning that enables users to leverage robotic control technology to navigate applications. With just minimal programming, users can control the functioning of robots across multiple deployments. Realtime Robotics raised US$31.4 million in its Series A round. The funding was led by HAHN Automation for the purpose of improving robotic capabilities.

2. Verve Motion

Verve Motion pioneers connected wearable technology for the industrial sector. It accompanies robotics into functional apparel and boosts worker safety and wellbeing with their technology. The company recently announced that it has raised US$15 million in Series A funding which was led by Construct Capital along with Founder Collective, Pillar VC, Safar Partners, OUP, and other angel investors.

3. Seoul Robotics

Seoul Robotics is a 3D computer vision company that innovates intelligent robotic perception systems using artificial intelligence and machine learning. The company’s first commercial model, Discovery, made its debut in the US market, earlier this year. It is an all-in-one sensor and software platform that expands access, reduces costs, and simplifies the implementation of LiDAR-powered solutions in several applications for smart cities, smart, factories, and logistic mobility. Seoul Robotics was selected as an Innovative Icon startup for all its efforts and received a US$12 million investment from the Korean Government.

4. Fetch Robotics

Not so much of an investment, but a business firm, Zebra Technologies is planning to acquire Fetch Robotics, a cloud-driven autonomous mobile robot startup. This acquisition aims to boost Zebra Technologies Enterprise Asset Intelligence vision and growth in industrial automation. This will align with Zebra Technology’s focus on robotics and change the infrastructure of the industry with seamless integration.

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From voice assistants to self-driving cars, artificial intelligence and machine learning are overtaking every aspect of the industrial sector. Machine learning algorithms are used to automate laborious tasks in businesses to discover patterns in existing data without being explicitly programmed.

The field is continuously evolving and high-value predictions are being used to make better decisions in real-time without human interventions. Under recent circumstances, investments in machine learning companies have drastically increased. Analytics Insight presents the top machine learning funding and investments in Q2 2021.

Lambda Labs

Amount Raised: US$15M

Transaction Type: Not Specified

Key Investor(s): Bloomberg, Patrick Collison, and others

Lambda provides deep learning services to top tech companies like Apple, Microsoft, MIT, and others. It is an AI infrastructure providing computation to accelerate human progress.

Zeitworks

Amount Raised: US$2M

Transaction Type: Not specified

Key Investor(s): Madrona Venture Group and Jazz Venture Partners

The company’s SaaS platform leverages machine learning to discover, analyze, and improve clients’ business processes without interfering with users or requiring system integrations. Their solutions measure the problems faced by the clients and execute step-by-step processes to solve the issues.

Deep Instinct

Amount Raised: US$67M

Transaction Type: Series D

Key Investor(s): Chrysalis Investments

The company uses deep learning algorithms to provide cybersecurity services. Deep Instinct’s on-device solution protects against zero-day threats and APT attacks with unparallel accuracy. By applying deep learning technology, enterprises can gain unmatched protection against cyber threats.

Physna

Amount Raised: US$56M

Transaction Type: Series B

Key Investor(s): Tiger Global, Sequoia Capital, and others

Physna is a geometric deep-learning and 3D search company that focuses on comparing and analyzing 3D models. The company powers innovation in manufacturing by bridging the gap between physical objects and digital codes.

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These Artificial Intelligence Companies, Now have the Funding to Innovate

The rate at which artificial intelligence is advancing is shaping the world around us. From automation to drug development and diagnosis, there is no industry that AI has not taken over. Like the silver lining to a dark cloud, the chaos created by COVID-19 pandemic has made organizations realize the power of artificial intelligence and are gearing up to invest heavily. Many renowned investors and Fortune 500 companies are also backing up budding AI companies that show promising growth potential. For the month of June in 2021, these are the AI companies that received heavy funding. For information on AI investments in April and May, check out this link.  

Top AI funding in June

CoffeeMug.ai

Transaction type: Pre-seed

Key investor(s): Paradigm Shift Capital and AngelList India

Singapore based AI professional networking platform, CoffeeMug.ai has raised US$625,000 in pre-seed funding round. Govind Mundhra, Founding General Partner of Paradigm Shift Capital, one of the key investors, will be joining the board of directors of CoffeeMug.ai. As per official reports, CoffeeMug will use these funds to accelerate its efforts to improve its AI-based matchmaking algorithm, double its user base and connect them with leadership level business opportunities.

Upside AI

Transaction type: Seed money

Key investor: Endiya Partners

Mumbai-based investment management startup, Upside AI, raised US$1.2 million in seed funding. Led by venture capital fund Endiya Partners, Upside AI plans to use the funds to fill up leadership positions and other senior roles. According to its cofounder Atanuu Agarrwal, the company intends to add 1,000 high net worth individuals, family offices, and institutional clients.

Eightfold AI

Transaction type: Series E

Key investors: SoftBank Vision

Eightfold AI is a talent-based intelligence platform provider based out of California. In the Series E funding round led by SoftBank Vision, with participation from General Catalyst, Capital One Ventures, Foundation Capital, IVP, and Lightspeed Venture Partners, Eightfold AI raised US$220 million. The company intends to use the total funding to promote further growth and development, and expand its partner ecosystem.

Gloat

Transaction type: Series C
Key investor(s): Accel, Eight Roads Ventures, Intel Capital, Magma, PICO

Gloat is an AI-enabled talent marketplace platform. Headquartered in New York, Gloat has expanded its offices globally, with an R&D center in Tel Aviv. The company assists companies in connecting their employees with development opportunities like projects and mentorship programs. In a Series C funding round co-led by Accel, Eight Roads Ventures, Intel Capital, Magma Venture Partners, and PICO partners, Gloat raised US$57 million which will be used to accelerate product innovation.

Cleerly

Transaction type: Series B

Key investor: Vensana Capital

Cleerly is a New York City-based company, that uses AI and machine learning algorithms to diagnose coronary artery disease. The company has developed a software platform that facilitates whole-heart quantification and characterization of atherosclerosis. Unlike traditional techniques that take hours, Cleerly’s software can perform the diagnosis in a matter of minutes, noninvasively. Led by Vensana Capital, Cleerly raised US$43 million in Series B funding, which will be used to scale its commercial reach, expand capabilities, strategic partnerships, and focus on R&D.

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Deep Instinct, the first and only cybersecurity company to successfully apply end-to-end deep learning to predict, identify, and prevent cyberattacks, announced its $43 million Series C funding. The round was led by Millennium New Horizons, with participation from Unbound, the London-based investment firm founded by Shravin Mittal, along with LG, and existing investor NVIDIA. Deep Instinct now counts four of the world’s largest technology companies amongst its investors, with HP Inc. and Samsung having participated in previous financing rounds. The investment, which brings the company’s total funding to $100 million, will be used to accelerate sales and marketing, as well as to support the expansion of business operations globally.

“Traditional cybersecurity is broken,” said Guy Caspi, co-founder and CEO of Deep Instinct. “Current solutions based on ‘assume breach’ are simply insufficient for the highly sophisticated attack landscape we all face. Deep Instinct takes an entirely new approach, preventing attacks before they are executed.”

Unlike traditional security solutions that primarily guard against known threats in the Windows operating system and help identify a cyberattack once it has already breached a system, Deep Instinct uses a patented deep learning platform trained to identify and prevent first-seen, sophisticated and advanced cyber threats. Threats are prevented anywhere within the enterprise from any type of file-based or file-less cyber attacks in zero-time, with unmatched accuracy and speed.

Deep Instinct’s deep learning protection has the lowest level of false positives of any cybersecurity provider. It is inclusive of physical and virtual networks, endpoints, and mobile, across multiple operating systems (Windows, iOS, Android, Chrome OS, and macOS).

“This significant round of new funding highlights the importance of prevention for every enterprise. The economic impact of repairing a breach is too high to ignore the need to prevent threats before they occur. The message to the market is that to fight today’s cyber threats true prevention will become more critical than detection and response.” said Lane Bess, Deep Instinct’s Chairman.

“There is no shortage of cybersecurity software providers, yet no company aside from Deep Instinct has figured out how to apply deep learning to automate malware analysis,” said Ray Cheng, Partner at Millennium New Horizons. “What excites us most about Deep Instinct is its proven ability to use its proprietary neural network to effectively detect viruses and malware no other software can catch. That genuine protection in an age of escalating threats, without the need of exorbitantly expensive or complicated systems, is a paradigm change.”

Deep Instinct recently announced an OEM partnership with HP Inc. to launch HP Sure Sense, on HP’s latest EliteBook and ZBook devices. By leveraging Deep Instinct’s deep learning threat prevention engine, HP Sure Sense provides zero-time detection and prevention against the most advanced cyber threats.

“Artificial intelligence is now sweeping across industries, bringing benefits to a wide range of vertical markets,” said Jeff Herbst, Vice President of Business Development at NVIDIA. “Deep Instinct’s unique approach in applying true deep learning to cybersecurity is yielding revolutionary breakthroughs that are being embraced by a growing market.”

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Pecan.ai, a startup that wants to help business analysts build machine learning models in an automated fashion, emerged from stealth today and announced an $11 million Series A.

The round was led by Dell Technologies Capital and S Capital. Along with a previously unannounced $4 million seed round, the company has raised a total of $15 million.

CEO Zohar Bronfman says he and co-founder Noam Brezis, whom he has known for more than a decade, started the company with the goal of building an automated machine learning platform. They observed that much of the work involved in building machine learning models is about getting data in a form that the algorithm can consume, something they’ve automated in Pecan.

“The innovative thing about Pecan is that we do all of the data preparation and data, engineering and data processing, and [complete the] various technical steps [for you],” Bronfman explained.

The target user is a business analyst using business intelligence and analytics tools, who wants to bring the power of machine learning to their data analysis, but lacks the skills to do it. “The business analyst knows the data very well, knows the business problem very well and speaks directly to the business owner of the problem — and they are currently conducting basic analytics,” he said.

Pecan includes a series of templates designed to answer common business questions. They divide these into two main categories. The first is customer questions like how much churn do we have, and the second is business operations questions related to things like risk or fraud. If the question doesn’t fall into one of these categories, it is possible to build your own template, but Bronfman says that is really for more advanced users.

After you select the template and point to a data source such as a database, data lake or CRM repository, Pecan does the work of connecting to the source and pulling data into a dashboard. You can also export the algorithm for use in an external service or application, or Pecan can automatically update a data repository with data the algorithm is measuring, such as churn rate.

The founders have been building this platform since 2016, when they founded the company, and have been working with beta customers for the last 18 months or so. Today, they emerge from stealth and bring Pecan to market in earnest.

Bronfman plans to move to New York City and open a sales and marketing office in the U.S., while Brezis will remain in Tel Aviv and oversee engineering. It’s early days for this startup, but with $11 million in capital, it has a chance to take the product to market and see what happens.

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Machine learning is a complex process. You build a model, test it in laboratory conditions, then put it out in the world. After that, how do you monitor how well it’s tracking what you designed it to do? Arthur wants to help, and today it emerged from stealth with a new platform to help you monitor machine learning models in production.

The company also announced it had closed a $3.3 million seed round, which closed in August.

Arthur CEO and co-founder Adam Wenchel says that Arthur is analogous to a performance-monitoring platform like New Relic or DataDog, but instead of monitoring your systems, it’s tracking the performance of your machine learning models.

“We are an AI monitoring and explainability company, which means when you put your models in production, we let you monitor them to know that they’re not going off the rails, that you can explain what they’re doing, that they’re not performing badly and are not being totally biassed — all of the ways models can go wrong,” Wenchel explained.

Data scientists build machine learning models and test them in the lab, but as Wenchel says, when that model leaves the controlled environment of the lab, lots can go wrong, and it’s hard to keep track of that. “Models always perform well in the lab, but then you put them out in the real world and there is often a drop-off in performance — in fact, almost always. So being able to measure and monitor that is a capability people really need,” he said.

Interestingly enough, AWS announced a new model-monitoring tool last week as part of SageMaker Studio. IBM also announced a similar tool for models built on the Watson platform earlier this year, but Wenchel says the involvement of the big guys could work to his company’s advantage as his product is platform-agnostic. “Having a neutral third party for your monitoring that works equally well across stacks is going to be pretty valuable,” he said.

As for the funding, it was co-led by Work-Bench  and Index Ventures, with participation from Hunter Walk at Homebrew, Jerry Yang at AME Ventures and others.

Jonathan Lehr, a general partner at Work-Bench, sees a company with a lot of potential. “We regularly speak with ML executives from Fortune 1000 companies and one of their biggest concerns as they become more data-driven is model behavior in production. The Arthur platform is by far the best solution we’ve seen for AI monitoring and transparency…” he said.

The company, which is based in New York City, currently has 10 people. It launched in 2018, and has been heads-down working on the product since. Today marks the release of the product publicly.

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Duality Technologies, a leading provider of Privacy-Enhancing Data Science Solutions based on Homomorphic Encryption, announced it has raised $16 million in a Series A funding round. The strategic funding was led by Intel Capital with the participation of Hearst Ventures and continued support from existing investor Team8.

The Duality SecurePlus™ platform is the first market-ready solution addressing today’s most pressing data privacy challenges arising from enterprises’ need to collaborate on sensitive data by applying Machine Learning and AI-based analytics. As the data-driven economy expands rapidly in all market segments, Duality’s platform enables multiple parties to maximize data utility by collaborating on sensitive data while preserving privacy, in compliance with growing data privacy regulations.

Duality’s SecurePlus™ platform optimizes data science computations on homomorphically encrypted data, delivering scalable privacy-enhanced solutions addressing real-world market needs, and overcoming performance challenges which until recently were considered “impossible”. Privacy-preserving data science is critical in today’s world as numerous enterprises, across all regulated industries, work with partners on data analytics endeavors: from banks seeking to apply privacy-enhanced financial crime investigations across institutions and borders, to retailers and their supply chain partners interested in privacy-preserving data monetization collaborations, to scientists cooperating on rare diseases and genomics research. SecurePlus™ enables aggregating and analyzing highly sensitive data while preserving patients’ privacy and the collaborators’ IP.

“AI and Machine Learning are transforming countless industries, but they have also created new privacy challenges that regulation alone can’t solve,” said CEO and Co-Founder of Duality Technologies Dr. Alon Kaufman. “We are excited by the investment of Intel Capital, Hearst Ventures and Team8 in Duality, and look forward to collaborating with these industry leaders in delivering innovative Privacy-Enhanced solutions to the market. Our mission is to reconcile data utility and privacy while unlocking a whole new world of secure collaborative business opportunities for our customers.”

“The ability to secure data during analysis is a critical component in the future computation stack, specifically in the context of AI. Intel Capital has been following the space closely, and we are excited to see secure computing and homomorphic encryption becoming practical and broadly applicable,” said Anthony Lin, Vice President & Senior Managing Director of Intel Capital. “We believe privacy-preservation in AI and ML represents a huge market need, and we’re investing in Duality because of its unique founding team and world-leading expertise in both advanced cryptography and data science.” Investment Director, Roi Bar-Kat, led the investment for Intel Capital.

This funding comes in the wake of the recent collaboration between Duality and Intel: In June 2018, the two announced a collaborative effort to explore the security challenges of AI workloads using homomorphic encryption on Intel platforms with the goal of minimizing data exposure. In August 2019, Intel, Duality and other tech leaders convened the AI community for a homomorphic encryption (HE) standards workshop to accelerate market adoption of the technology across industries.

“As a leading global, diversified media, information and services company with more than 360 businesses across industries, we are acutely aware of the increasing importance of data and data collaboration in companies across many market segments,” said Kenneth Bronfin, Senior Managing Director of Hearst Ventures. “Sensitive data is constantly being generated by both individuals and businesses; there needs to be technology available that protects such data while allowing us to extract insights. We are excited by Duality’s mission and its ability to deliver complex technology to real-world use cases and applications.”

Duality was co-founded by scientific leaders including Turing Award winner Professor Shafi Goldwasser; MIT’s Prof. Vinod Vaikuntanathan, the co-inventor of the foundational BGV Homomorphic Encryption scheme; and Dr. Kurt Rohloff, founder of the PALISADE Homomorphic Encryption open source library on which Duality’s platform is based; together with Dr. Alon Kaufman, CEO, and Ms. Rina Shainski, Chairwoman. The outstanding expertise in cryptography is complemented by the team’s strong background in data science, powering Duality’s innovative approach to privacy-enhanced data science solutions.

Duality will leverage the funding to continue developing its secure computing platform, offering privacy-enhanced solutions addressing customer needs in a wide variety of market segments.

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