Personal blog of Yzmir Ramirez

UiPath came seemingly out of nowhere in the last several years, going public last year in a successful IPO during which it raised more than $527 million. It raised $2 billion in private money prior to that with its final private valuation coming in at an amazing $35 billion. UiPath CEO Daniel Dines will be joining us on a panel to discuss automation at TC Sessions: SaaS on October 27th.

The company has been able to capture all this investor attention doing something called robotic process automation (RPA), which provides a way to automate a series of highly mundane tasks. It has become quite popular, especially to help bring a level of automation to legacy systems that might not be able to handle more modern approaches to automation involving artificial intelligence and machine learning. In 2019 Gartner found that RPA was the fastest growing category in enterprise software.

In point of fact, UiPath didn’t actually come out of nowhere. It was founded in 2005 as a consulting company and transitioned to software over the years. The company took its first VC funding, a modest $1.5 million seed round, in 2015, according to Crunchbase data.

As RPA found its market, the startup began to take off, raising gobs of money, including a $568 million round in April 2019 and $750 million in its final private raise in February 2021.

Dines will be appearing on a panel discussing the role of automation in the enterprise. Certainly, the pandemic drove home the need for increased automation as masses of office workers moved to work from home, a trend that is likely to continue even after the pandemic slows.

As the RPA market leader, he is uniquely positioned to discuss how this software and other similar types will evolve in the coming years and how it could combine with related trends like no-code and process mapping. Dines will be joined on the panel by investor Laela Sturdy from CapitalG and ServiceNow’s Dave Wright, where they will discuss the state of the automation market, why it’s so hot and where the next opportunities could be.

In addition to our discussion with Dines, the conference will also include Databricks’ Ali Ghodsi, Salesforce’s Kathy Baxter and Puppet’s Abby Kearns, as well as investors Casey Aylward and Sarah Guo, among others. We hope you’ll join us. It’s going to be a stimulating day.

Buy your pass now to save up to $100. We can’t wait to see you in October!

Is your company interested in sponsoring or exhibiting at TC Sessions: SaaS 2021? Contact our sponsorship sales team by filling out this form.

Open-source business intelligence company Metabase announced Thursday a $30 million Series B round led by Insight Partners.

Existing investors Expa and NEA joined in on the round, which gives the San Francisco-based company a total of $42.5 million in funding since it was founded in 2015. Metabase previously raised $8 million in Series A funding back in 2019, led by NEA.

Metabase was developed within venture studio Expa and spun out as an easy way for people to interact with data sets, co-founder and CEO Sameer Al-Sakran told TechCrunch.

“When someone wants access to data, they may not know what to measure or how to use it, all they know is they have the data,” Al-Sakran said. “We provide a self-service access layer where they can ask a question, Metabase scans the data and they can use the results to build models, create a dashboard and even slice the data in ways they choose without having an analyst build out the database.”

He notes that not much has changed in the business intelligence realm since Tableau came out more than 15 years ago, and that computers can do more for the end user, particularly to understand what the user is going to do. Increasingly, open source is the way software and information wants to be consumed, especially for the person that just wants to pull the data themselves, he added.

George Mathew, managing director of Insight Partners, believes we are seeing the third generation of business intelligence tools emerging following centralized enterprise architectures like SAP, then self-service tools like Tableau and Looker and now companies like Metabase that can get users to discovery and insights quickly.

“The third generation is here and they are leading the charge to insights and value,” Mathew added. “In addition, the world has moved to the cloud, and BI tools need to move there, too. This generation of open source is a better and greater example of all three of those.”

To date, Metabase has been downloaded 98 million times and used by more than 30,000 companies across 200 countries. The company pursued another round of funding after building out a commercial offering, Metabase Enterprise, that is doing well, Al-Sakran said.

The new funding round enables the company to build out a sales team and continue with product development on both Metabase Enterprise and Metabase Cloud. Due to Metabase often being someone’s first business intelligence tool, he is also doubling down on resources to help educate customers on how to ask questions and learn from their data.

“Open source has changed from floppy disks to projects on the cloud, and we think end users have the right to see what they are running,” Al-Sakran said. “We are continuing to create new features and improve performance and overall experience in efforts to create the BI system of the future.

Houston-based ThirdAI, a company building tools to speed up deep learning technology without the need for specialized hardware like graphics processing units, brought in $6 million in seed funding.

Neotribe Ventures, Cervin Ventures and Firebolt Ventures co-led the investment, which will be used to hire additional employees and invest in computing resources, Anshumali Shrivastava, Third AI co-founder and CEO, told TechCrunch.

Shrivastava, who has a mathematics background, was always interested in artificial intelligence and machine learning, especially rethinking how AI could be developed in a more efficient manner. It was when he was at Rice University that he looked into how to make that work for deep learning. He started ThirdAI in April with some Rice graduate students.

ThirdAI’s technology is designed to be “a smarter approach to deep learning,” using its algorithm and software innovations to make general-purpose central processing units (CPU) faster than graphics processing units for training large neural networks, Shrivastava said. Companies abandoned CPUs years ago in favor of graphics processing units that could more quickly render high-resolution images and video concurrently. The downside is that there is not much memory in graphics processing units, and users often hit a bottleneck while trying to develop AI, he added.

“When we looked at the landscape of deep learning, we saw that much of the technology was from the 1980s, and a majority of the market, some 80%, were using graphics processing units, but were investing in expensive hardware and expensive engineers and then waiting for the magic of AI to happen,” he said.

He and his team looked at how AI was likely to be developed in the future and wanted to create a cost-saving alternative to graphics processing units. Their algorithm, “sub-linear deep learning engine,” instead uses CPUs that don’t require specialized acceleration hardware.

Swaroop “Kittu” Kolluri, founder and managing partner at Neotribe, said this type of technology is still early. Current methods are laborious, expensive and slow, and for example, if a company is running language models that require more memory, it will run into problems, he added.

“That’s where ThirdAI comes in, where you can have your cake and eat it, too,” Kolluri said. “It is also why we wanted to invest. It is not just the computing, but the memory, and ThirdAI will enable anyone to do it, which is going to be a game changer. As technology around deep learning starts to get more sophisticated, there is no limit to what is possible.”

AI is already at a stage where it has the capability to solve some of the hardest problems, like those in healthcare and seismic processing, but he notes there is also a question about climate implications of running AI models.

“Training deep learning models can be more expensive than having five cars in a lifetime,” Shrivastava said. “As we move on to scale AI, we need to think about those.”

Mobile field service startup Youreka Labs Inc. raised an $8.5 million Series A round of funding co-led by Boulder Ventures and Grotech Ventures, with participation from Salesforce Ventures.

The Maryland-based company also officially announced its CEO — Bill Karpovich joined to lead the company after previously general manager at IBM Cloud & Watson Platform.

Youreka Labs spun out into its own company from parent company Synaptic Advisors, a cloud consulting business focused on the customer relationship management transformations using Salesforce and other artificial intelligence and automation technologies.

The company is developing robotic smart mobile assistants that enable frontline workers to perform their jobs more safely and efficiently. This includes things like guided procedures, smart forms and photo or video capture. Youreka is also embedded in existing Salesforce mobile applications like Field Service Mobile so that end-users only have to operate from one mobile app.

Youreka has identified four use cases so far: healthcare, manufacturing, energy and utilities and the public sector. Working with companies like Shell, P&G, Humana and the Transportation Security Administration, the company’s technology makes it possible for someone to share their knowledge and processes with their colleagues in the field, Karpovich told TechCrunch.

“In the case of healthcare, we are taking complex medical assessments from a doctor and pushing them out to nurses out in the field by gathering data into a simple mobile app and making it useful,” he added. “It allows nurses to do a great job without being doctors themselves.”

Karpovich said the company went after Series A dollars because it was “time for it to be on its own.” He was receiving inbound interest from investors, and the capital would enable the company to proceed more rapidly. Today, the company is focused on the Salesforce ecosystem, but that can evolve over time, he added.

The funding will be used to expand the company’s reach and products. He expects to double the team in the next six to 12 months across engineering to be able to expand the platform. Youreka boasts 100 customers today, and Karpovich would also like to invest in marketing to grow that base.

In addition to the use cases already identified, he sees additional potential in financial services and insurance, particularly for those assessing damage. The company is also concentrated in the United States, and Karpovich has plans to expand in the U.K. and Europe.

In 2020, the company grew 300%, which Karpovich attributes to the need of this kind of tool in field service. Youreka has a licensing model with charges per end user per month, along with an administrative license, for the people creating the apps, that also charges per user and per month pricing.

“There are 2.5 million jobs open today because companies can’t find people with the right skills,” he added. “We are making these jobs accessible. Some say that AI is doing away with jobs, but we are using AI to enhance jobs. If we can take 90% of the knowledge and give a digital assistant to less experienced people, you could open up so many opportunities.”

Talkdesk, a provider of cloud-based contact center software, announced $230 million in new Series D funding that more than triples the company’s valuation to $10 billion, Talkdesk founder CEO Tiago Paiva confirmed to TechCrunch.

New investors Whale Rock Capital Management, TI Platform Management and Alpha Square Group came on board for this round and were joined by existing investors Amity Ventures, Franklin Templeton, Top Tier Capital Partners, Viking Global Investors and Willoughby Capital.

Talkdesk uses artificial intelligence and machine learning to improve customer service for midmarket and enterprise businesses. It counts over 1,800 companies as customers, including IBM, Acxiom, Trivago and Fujitsu.

“The global pandemic was a big part of how customers interact and how we interacted with our customers, all working from home,” Paiva said. “When you think about ordering things online, call, chat and email interactions became more important, and contact centers became core in every company.”

San Francisco-based Talkdesk now has $498 million in total funding since its inception in 2011. It was a Startup Battlefield contestant at TechCrunch Disrupt NY in 2012. The new funding follows a $143 million Series C raised last July that gave it a $3 billion valuation. Prior to that, Talkdesk brought in $100 million in 2018.

The 2020 round was planned to buoy the company’s growth and expansion to nearly 2,000 employees, Paiva said. For the Series D, there was much interest from investors, including a lot of inbound interest, he said.

“We were not looking for new money, and finished last year with more money in the bank that we raised in the last round, but the investors were great and wanted to make it work,” Paiva said.

Half of Talkdesk’s staff is in product and engineering, an area he intends to double down in with the new funding as well as adding to the headcount to support customers. The company also has plans to expand in areas where it is already operating — Latin America, Europe, Asia and Australia.

This year, the company unveiled new features, including Talkdesk Workspace, a customizable interface for contact center teams, and Talkdesk Builder, a set of tools for customization across workspaces, routing, reporting and integrations. It also launched contact center tools designed specifically for financial services and healthcare organizations and what it is touting as the “industry’s first human-in-the-loop tool for contact centers and continues to lower the barrier to adopting artificial intelligence solutions.”

In addition to the funding, Talkdesk appointed its first chief financial officer, Sydney Carey, giving the company an executive team of 50% women, Paiva said. Carey has a SaaS background and joins the company from Sumo Logic, where she led the organization through an initial public offering in 2020.

“We were hiring our executive team over the past couple of years, and were looking for a CFO, but with no specific timeline, just looking for the right person,” Paiva added. “Sydney was the person we wanted to hire.”

Though Paiva didn’t hint at any upcoming IPO plans, TI Platform Management co-founders Trang Nguyen and Alex Bangash have followed Paiva since he started the company and said they anticipate the company heading in that direction in the future.

“Talkdesk is an example of what can happen when a strong team is assembled behind a winning idea,” they said in a written statement. “Today, Talkdesk has become near ubiquitous as a SaaS product with adoption across a broad array of industries and integrations with the most popular enterprise cloud platforms, including Salesforce, Zendesk and Slack.”

As the use of AI has grown and developed over the last several years, companies like Salesforce have tried to tap into it to improve their software and help customers operate faster and more efficiently. Kathy Baxter, principal architect for the ethical AI practice at Salesforce, will be joining us at TechCrunch Sessions: SaaS on October 27th to talk about the impact of AI on SaaS.

Baxter, who has more than 20 years of experience as a software architect, joined Salesforce in 2017 after more than a decade at Google in a similar role. We’re going to tap into her expertise on a panel discussing AI’s growing role in software.

Salesforce was one of the earlier SaaS adherents to AI, announcing its artificial intelligence tooling, which the company dubbed Einstein, in 2016. While the positioning makes it sound like a product, it’s actually much more than a single entity. It’s a platform component, which the various pieces of the Salesforce platform can tap into to take advantage of various types of AI to help improve the user experience.

That could involve feeding information to customer service reps on Service Cloud to make the call move along more efficiently, helping salespeople find the customers most likely to close a deal soon in the Sales Cloud or helping marketing understand the optimal time to send an email in the Marketing Cloud.

The company began building out its AI tooling early on with the help of 175 data scientists and has been expanding on that initial idea since. Other companies, both startups and established companies like SAP, Oracle and Microsoft, have continued to build AI into their platforms as Salesforce has. Today, many SaaS companies have some underlying AI built into their service.

Baxter will join us to discuss the role of AI in software today and how that helps improve the operations of the service itself, and what the implications are of using AI in your software service as it becomes a mainstream part of the SaaS development process.

In addition to our discussion with Baxter, the conference will also include Databricks’ Ali Ghodsi, UiPath’s Daniel Dines and Puppet’s Abby Kearns, as well as investors Casey Aylward and Sarah Guo, among others. We hope you’ll join us. It’s going to be a stimulating day.

Buy your pass now to save up to $100, and use CrunchMatch to make expanding your empire quick, easy and efficient. We can’t wait to see you in October!

Is your company interested in sponsoring or exhibiting at TC Sessions: SaaS 2021? Contact our sponsorship sales team by filling out this form.

Upscribe founder and CEO Dileepan Siva watched the retail industry make a massive shift to subscription e-commerce for physical products over the past decade, and decided to get in it himself in 2019.

The Los Angeles-based company, developing subscription software for direct-to-consumer e-commerce merchants, is Siva’s fourth startup experience and first time as founder. He closed a $4 million seed round to go after two macro trends he is seeing: buying physical products, like consumer-packaged goods, on a recurring basis, and new industries offering subscriptions, like car and fashion companies.

Merchants use Upscribe’s technology to drive subscriber growth, reduce churn and enable their customers to personalize a subscription experience, like skipping shipments, swapping out products and changing the order frequency. Brands can also feature products for upsell purposes throughout the subscriber lifecycle, from checkout to post-purchase.

Upscribe also offers APIs for merchants to integrate tools like Klaviyo, Segment and Shopify — a new subscription offering for checkouts.

Uncork Capital led the seed round and was joined by Leaders Fund, The House Fund, Roach Capitals’ Fahd Ananta and Shippo CEO Laura Behrens Wu.

“As the market for D2C subscriptions booms, there is a need for subscription-first brands to grow and scale their businesses,” said Jeff Clavier, founder and managing partner of Uncork Capital, in a written statement. “We have spent a long time in the e-commerce space, working with D2C brands and companies who are solving common industry pain points, and Upscribe’s merchant-centric approach raised the bar for subscription services, addressing the friction in customer experiences and enabling merchants to engage subscribers and scale recurring revenue growth.”

Siva bootstrapped the company, but decided to go after venture capital dollars when Upscribe wanted to create a more merchant-centric approach, which required scaling with a bigger team. The “real gems are in the data layer and how to make the experience exceptional,” he added.

The company is growing 43% quarter over quarter and is close to profitable, with much of its business stemming from referrals, Siva said. It is already working with customers like Athletic Greens, Four Sigmatic and True Botanicals and across multiple verticals, including food and beverage, health and wellness, beauty and cosmetics and home care.

The new funding will be used to “capture the next wave of brands that are going to grow,” he added. Siva cites the growth will come as the DTC subscription market is forecasted to reach $478 billion by 2025, and 75% of those brands are expected to offer subscriptions in the next two years. As such, the majority of the funding will be used to bring on more employees, especially in the product, customer success and go-to-market functions.

Though there is competition in the space, many of those are focused on processing transactions, while Siva said Upscribe’s approach is customer relationships. The cost of acquiring new customers is going up, and subscription services will be the key to converting one-time buyers into loyal customers.

“It is really about customer relationships and the ongoing engagement between merchants and subscribers,” he added. “We are in a different world now. The first wave could play the Facebook game, advertising on social media with super low acquisition and scale. That is no longer the case anymore.”

Two decades after businesses first started deploying AI solutions, one can argue that they’ve made little progress in achieving significant gains in efficiency and profitability relative to the hype that drove initial expectations.

On the surface, recent data supports AI skeptics. Almost 90% of data science projects never make it to production; only 20% of analytics insights through 2022 will achieve business outcomes; and even companies that have developed an enterprisewide AI strategy are seeing failure rates of up to 50%.

But the past 25 years have only been the first phase in the evolution of enterprise AI — or what we might call Enterprise AI 1.0. That’s where many businesses remain today. However, companies on the leading edge of AI innovation have advanced to the next generation, which will define the coming decade of big data, analytics and automation — Enterprise AI 2.0.

The difference between these two generations of enterprise AI is not academic. For executives across the business spectrum — from healthcare and retail to media and finance — the evolution from 1.0 to 2.0 is a chance to learn and adapt from past failures, create concrete expectations for future uses and justify the rising investment in AI that we see across industries.

Two decades from now, when business leaders look back to the 2020s, the companies who achieved Enterprise AI 2.0 first will have come to be big winners in the economy, having differentiated their services, scooped up market share and positioned themselves for ongoing innovation.

Framing the digital transformations of the future as an evolution from Enterprise AI 1.0 to 2.0 provides a conceptual model for business leaders developing strategies to compete in the age of automation and advanced analytics.

Enterprise AI 1.0 (the status quo)

Starting in the mid-1990s, AI was a sector marked by speculative testing, experimental interest and exploration. These activities occurred almost exclusively in the domain of data scientists. As Gartner wrote in a recent report, these efforts were “alchemy … run by wizards whose talents will not scale in the organization.”

One year after raising $16 million, construction technology company Buildots is back to claim another $30 million, this time in Series B funding.

Lightspeed Venture Partners led the round, with participation from previous investors TLV Partners, Future Energy Ventures, Tidhar Construction Group and Maor Investments. This gives the company $46 million in total funding, Roy Danon, co-founder and CEO of Buildots, told TechCrunch.

The three-year-old company, with headquarters in Tel Aviv and London, is leveraging artificial intelligence computer vision technology to address construction inefficiencies. Danon said though construction accounts for 13% of the world’s GDP and employs hundreds of millions of people, construction productivity continues to lag, only growing 1% in the past two decades.

Danon spent six months on construction sites talking to workers to understand what was happening and learned that control was one of the areas where efficiency was breaking down. While construction processes would seem similar to manufacturing processes, building to the design or specs didn’t happen often due to different rules and reliance on numerous entities to get their jobs done first, he said.

Buildots’ technology is addressing this gap using AI algorithms to automatically validate images captured by hardhat-mounted 360-degree cameras, detecting immediately any gaps between the original design, scheduling and what is actually happening on the construction site. Project managers can then make better decisions to speed up construction.

“It even finds events where contractors are installing out of place and streamline payments so that information is transparent and clear,” Danon said. “Buildots also creates a collaborative environment and trust by having a single source telling everyone what is going on. There is no more blaming or cutting corners because the system validates that and also makes construction a healthier industry to work in.”

Buildots went after new funding once it was able to show product market fit and was expanding into other countries. The platform is being utilized on major building projects in countries like the U.S., U.K., Germany, Switzerland, Scandinavia and China. To meet demand, Buildots will use the new funding to continue that expansion; double the size of its global team with a focus on sales, marketing and R&D; and grow on the business side. Danon’s aim is “to get to the point where we are the standard for every construction site.” The company is also looking at areas outside construction where its technology would be applicable.

Tal Morgenstern, partner at Lightspeed Venture Partners, said he keeps an eye on graduates of the Israel Defense Forces, where the three Buildots founders came from. However, in the case of this company, Lightspeed actually passed on both the seed and Series A.

Morgenstern admits the decision was a mistake, but at the time, he thought the technology Buildots was trying to build “first, impossible and second, I knew construction was difficult to sell into.” He felt that Buildots, with such a premium product, would have a challenge selling to a low-margin industry that was late to adopt technology in general.

By the time the Series B came round, he said Buildots had solved both of those issues, proving that it works, but also that customers were adopting the technology without much sales and marketing. In addition, other solutions in construction tech were still relying on lasers or people to manually input or tap photos.

“Buildots is seamlessly capturing images and providing a level of insights that is so high, and that is why the company is able to command the price structure they have and are receiving interesting commercial results,” Morgenstern said.

Walking around today’s construction site, Danon said the adoption of technology is enabling Buildots to move quickly to build processes for the industry.

As such, the company saw more than 50% growth quarter over quarter over the past year in three of the countries in which it operates. It is now working with four of the top 10 construction companies in Europe and around the world.

“We did a good job selling remotely, but now we need local offices,” Danon added. “We are also sitting on piles of data from construction sites. We learn from one project to another and want to look for the challenges where data will help make a financial impact. It’s a natural next step for the company.”

Correlated on Wednesday announced it raised $8.3 million in seed funding to launch its product-led growth platform for sales teams.

NextView Ventures and Harrison Metal co-led the round and were joined by Apollo Projects, Attentive co-founders Brian Long and Andrew Jones, Cockroach Labs co-founder Ben Darnell and Atrium’s Pete Kazanjy. The round includes funding raised last year and more recent follow-on funding from both NextView and Harrison, co-founder and CEO Tim Geisenheimer told TechCrunch.

The New York-based company was founded in 2020 by Geisenheimer and Diana Hsieh, who overlapped at TimescaleDB, and John Pena, who Geisenheimer met at Facet. In their previous roles, they saw a need to connect product data to sales tools.

While at Timescale, Geisenheimer said there were thousands of free users to talk to, and he and Hsieh built a similar version of a product-led growth platform there, but secretly wished there was something more like Correlated available.

What they saw was data across multiple tools being stored manually on spreadsheets so that actionable insights could be generated. The data would quickly become outdated. Add in that the way customers use products now is different. Traditionally, customers would not be able to use a product until they talked to the sales team. Today, customers start using products for free and either get value from it or not, but sales teams don’t have real-time data on their experience.

“Sales needs to know how customers are using the product and the right time for sales to engage based on maturity of the experience,” Geisenheimer said. “That was the missing piece of it and sales teams ended up talking to the wrong people. With Correlated, they can close more deals efficiently.”

Correlated’s technology pulls in product usage data from tools and data warehouses and connects to a management platform like Salesforce or HubSpot, stitching it together into a data graph to show how customers are using a product. For example, within a company of 200 to 500 employees, a salesperson can see the frequency employees logged in and be alerted of when the best opportunity is to make the sale.

The company has a SaaS pricing model and is already working with mid-market companies like Ally, Pulumi, ReadMe and LaunchNotes. To support its launch out of beta, Geisenheimer intends to use the new funding for hiring across functions like engineering and go-to-market. The company has 11 employees currently.

There are other product-led growth platforms out there that raised venture capital funding recently, for example, Endgame, and similarly Geisenheimer said the competition is often in-house product teams building their own systems. Correlated’s differentiator is that it has taken on that task itself and enables customers to quickly see value once they are up-and-running, he added.

David Beisel, co-founder and partner at NextView Ventures, said his firm invests in category stage companies and is currently operating out of its fourth fund, infusing business-to-business SaaS and e-commerce companies. Beisel has known Geisenheimer for nearly a decade now, having met him when NextView invested in one of Geisenheimer’s previous companies, TapCommerce.

“At the end of the day with Tim, he knows sales and the company is selling a product that has a strong founder market fit,” Beisel said. “We are moving toward a world where end-user adoption of software — not the initial engagement — is growing over time. Instead, Correlated empowers that initial sale and account expansion and that will align with where the industry is going.”