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!

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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.

Reliance on a single technology as a lifeline is a futile battle now. When simple automation no longer does the trick, delivering end-to-end automation needs a combination of complementary technologies that can give a facelift to business processes: the digital operations toolbox.

According to a McKinsey survey, enterprises that have likely been successful with digital transformation efforts adopted sophisticated technologies such as artificial intelligence, Internet of Things or machine learning. Enterprises can achieve hyperautomation with the digital ops toolbox, the hub for your digital operations.

The toolbox is a synchronous medley of intelligent business process management (iBPM), robotic process automation (RPA), process mining, low code, artificial intelligence (AI), machine learning (ML) and a rules engine. The technologies can be optimally combined to achieve the organization’s key performance indicator (KPI) through hyperautomation.

The hyperautomation market is burgeoning: Analysts predict that by 2025, it will reach around $860 billion. Let’s see why.

The purpose of a digital ops toolbox

The toolbox, the treasure chest of technologies it is, helps with three crucial aspects: process automation, orchestration and intelligence.

Process automation: A hyperautomation mindset introduces the world of “automating anything that can be,” whether that’s a process or a task. If something can be handled by bots or other technologies, it should be.

Orchestration: Hyperautomation, per se, adds an orchestration layer to simple automation. Technologies like intelligent business process management orchestrate the entire process.

Intelligence: Machines can automate repetitive tasks, but they lack the decision-making capabilities of humans. And, to achieve a perfect harmony where machines are made to “think and act,” or attain cognitive skills, we need AI. Combining AI, ML and natural language processing algorithms with analytics propels simple automation to become more cognitive. Instead of just following if-then rules, the technologies help gather insights from the data. The decision-making capabilities enable bots to make decisions.

Simple automation versus hyperautomation

Here’s a story of evolving from simple automation to hyperautomation with an example: an order-to-cash process.

Robotic process automation has become buzzy in the last few months. New York-based UiPath is on course to launch an initial public offering after gaining an astounding valuation of $35 billion in February. Over in China, homegrown RPA startup Laiye is making waves as well.

Laiye, which develops software to mimic mundane workplace tasks like keyboard strokes and mouse clicks, announced it has raised $50 million in a Series C+ round. The proceeds came about a year after the Beijing-based company pulled in the first tranche of its Series C round.

Laiye, six years old and led by Baidu veterans, has raised over $130 million to date according to public information.

Leading investors in the Series C+ round were Ping An Global Voyager Fund, an early-stage strategic investment vehicle of Chinese financial conglomerate Ping An, and Shanghai Artificial Intelligence Industry Equity Investment Fund, a government-backed fund. Other participants included Lightspeed China Partners, Lightspeed Venture Partners, Sequoia China and Wu Capital.

RPA tools are attracting companies looking for ways to automate workflows during COVID-19, which has disrupted office collaboration. But the enterprise tech was already gaining traction prior to the pandemic. As my colleague Ron Miller wrote this month on the heels of UiPath’s S1 filing:

“The category was gaining in popularity by that point because it addressed automation in a legacy context. That meant companies with deep legacy technology — practically everyone not born in the cloud — could automate across older platforms without ripping and replacing, an expensive and risky undertaking that most CEOs would rather not take.”

In one case, Laiye’s RPA software helped the social security workers in the city of Lanzhou speed up their account reconciliation process by 75%; in the past, they would have to type in pensioners’ information and check manually whether the details were correct.

In another instance, Laiye’s chatbot helped automate the national population census in several southern Chinese cities, freeing census takers from visiting households door-to-door.

Laiye said its RPA enterprise business achieved positive cash flow and its chatbot business turned profitability in the fourth quarter of 2020. Its free-to-use edition has amassed over 400,000 developers, and the company also runs a bot marketplace connecting freelance developers to small-time businesses with automation needs.

Laiye is expanding its services globally and boasts that its footprint now spans Asia, the United States and Europe.

“Laiye aims to foster the world’s largest developer community for software robots and built the world’s largest bot marketplace in the next three years, and we plan to certify at least one million software robot developers by 2025,” said Wang Guanchun, chair and CEO of Laiye.

“We believe that digital workforce and intelligent automation will reach all walks of life as long as more human workers can be up-skilled with knowledge in RPA and AI”.

Berlin-based y42 (formerly known as Datos Intelligence), a data warehouse-centric business intelligence service that promises to give businesses access to an enterprise-level data stack that’s as simple to use as a spreadsheet, today announced that it has raised a $2.9 million seed funding round led by La Famiglia VC. Additional investors include the co-founders of Foodspring, Personio and Petlab.

The service, which was founded in 2020, integrates with more than 100 data sources, covering all the standard B2B SaaS tools, from Airtable to Shopify and Zendesk, as well as database services like Google’s BigQuery. Users can then transform and visualize this data, orchestrate their data pipelines and trigger automated workflows based on this data (think sending Slack notifications when revenue drops or emailing customers based on your own custom criteria).

Like similar startups, y42 extends the idea data warehouse, which was traditionally used for analytics, and helps businesses operationalize this data. At the core of the service is a lot of open source and the company, for example, contributes to GitLabs’ Meltano platform for building data pipelines.

y42 founder and CEO Hung Dang. Image Credits: y42

“We’re taking the best of breed open-source software. What we really want to accomplish is to create a tool that is so easy to understand and that enables everyone to work with their data effectively,” Y42 founder and CEO Hung Dang told me. “We’re extremely UX obsessed and I would describe us as a no-code/low-code BI tool — but with the power of an enterprise-level data stack and the simplicity of Google Sheets.”

Before y42, Vietnam-born Dang co-founded a major events company that operated in more than 10 countries and made millions in revenue (but with very thin margins), all while finishing up his studies with a focus on business analytics. And that in turn led him to also found a second company that focused on B2B data analytics.

Image Credits: y42

Even while building his events company, he noted, he was always very product- and data-driven. “I was implementing data pipelines to collect customer feedback and merge it with operational data — and it was really a big pain at that time,” he said. “I was using tools like Tableau and Alteryx, and it was really hard to glue them together — and they were quite expensive. So out of that frustration, I decided to develop an internal tool that was actually quite usable and in 2016, I decided to turn it into an actual company. ”

He then sold this company to a major publicly listed German company. An NDA prevents him from talking about the details of this transaction, but maybe you can draw some conclusions from the fact that he spent time at Eventim before founding y42.

Given his background, it’s maybe no surprise that y42’s focus is on making life easier for data engineers and, at the same time, putting the power of these platforms in the hands of business analysts. Dang noted that y42 typically provides some consulting work when it onboards new clients, but that’s mostly to give them a head start. Given the no-code/low-code nature of the product, most analysts are able to get started pretty quickly — and for more complex queries, customers can opt to drop down from the graphical interface to y42’s low-code level and write queries in the service’s SQL dialect.

The service itself runs on Google Cloud and the 25-people team manages about 50,000 jobs per day for its clients. The company’s customers include the likes of LifeMD, Petlab and Everdrop.

Until raising this round, Dang self-funded the company and had also raised some money from angel investors. But La Famiglia felt like the right fit for y42, especially due to its focus on connecting startups with more traditional enterprise companies.

“When we first saw the product demo, it struck us how on top of analytical excellence, a lot of product development has gone into the y42 platform,” said Judith Dada, general partner at LaFamiglia VC. “More and more work with data today means that data silos within organizations multiply, resulting in chaos or incorrect data. y42 is a powerful single source of truth for data experts and non-data experts alike. As former data scientists and analysts, we wish that we had y42 capabilities back then.”

Dang tells me he could have raised more but decided that he didn’t want to dilute the team’s stake too much at this point. “It’s a small round, but this round forces us to set up the right structure. For the Series A, which we plan to be towards the end of this year, we’re talking about a dimension which is 10x,” he told me.

DeepSee.ai, a startup that helps enterprises use AI to automate line-of-business problems, today announced that it has raised a $22.6 million Series A funding round led by led by ForgePoint Capital. Previous investors AllegisCyber Capital and Signal Peak Ventures also participated in this round, which brings the Salt Lake City-based company’s total funding to date to $30.7 million.

The company argues that it offers enterprises a different take on process automation. The industry buzzword these days is “robotic process automation,” but DeepSee.ai argues that what it does is different. I describe its system as “knowledge process automation” (KPA). The company itself defines this as a system that “mines unstructured data, operationalizes AI-powered insights, and automates results into real-time action for the enterprise.” But the company also argues that today’s bots focus on basic task automation that doesn’t offer the kind of deeper insights that sophisticated machine learning models can bring to the table. The company also stresses that it doesn’t aim to replace knowledge workers but helps them leverage AI to turn into actionable insights the plethora of data that businesses now collect.

Image Credits: DeepSee.ai

“Executives are telling me they need business outcomes and not science projects,” writes DeepSee.ai CEO Steve Shillingford. “And today, the burgeoning frustration with most AI-centric deployments in large-scale enterprises is they look great in theory but largely fail in production. We think that’s because right now the current ‘AI approach’ lacks a holistic business context relevance. It’s unthinking, rigid and without the contextual input of subject-matter experts on the ground. We founded DeepSee to bridge the gap between powerful technology and line-of-business, with adaptable solutions that empower our customers to operationalize AI-powered automation — delivering faster, better and cheaper results for our users.”

To help businesses get started with the platform, DeepSee.ai offers three core tools. There’s DeepSee Assembler, which ingests unstructured data and gets it ready for labeling, model review and analysis. Then, DeepSee Atlas can use this data to train AI models that can understand a company’s business processes and help subject-matter experts define templates, rules and logic for automating a company’s internal processes. The third tool, DeepSee Advisor, meanwhile focuses on using text analysis to help companies better understand and evaluate their business processes.

Currently, the company’s focus is on providing these tools for insurance companies, the public sector and capital markets. In the insurance space, use cases include fraud detection, claims prediction and processing, and using large amounts of unstructured data to identify patterns in agent audits, for example.

That’s a relatively limited number of industries for a startup to operate in, but the company says it will use its new funding to accelerate product development and expand to new verticals.

“Using KPA, line-of-business executives can bridge data science and enterprise outcomes, operationalize AI/ML-powered automation at scale, and use predictive insights in real time to grow revenue, reduce cost and mitigate risk,” said Sean Cunningham, managing director of ForgePoint Capital. “As a leading cybersecurity investor, ForgePoint sees the daily security challenges around insider threat, data visibility and compliance. This investment in DeepSee accelerates the ability to reduce risk with business automation and delivers much-needed AI transparency required by customers for implementation.”

As the pandemic drags on and we learn about the requirements of working from home with distributed teams, users could be craving more integration across their tools to help reduce the clicks required to complete a set of tasks. Today at the Ignite Conference, Microsoft announced tighter integration between its business suite Dynamics 365 and its collaboration tool Teams to help with that issue.

Alysa Taylor, corporate VP for business applications and global industry at Microsoft, pointed out that one of the advantages of this native integration approach is that it helps reduce context switching across different applications. “We are committed to really bringing together the collaboration platform and the business process layer to enable salespeople, service representatives, operations managers [and other similar roles] to really have a unified platform in which they both collaborate and have their everyday business functions,” Taylor explained.

This could manifest itself in a number of different ways across marketing, sales and service. For instance, a marketer can create a webinar, which they set up and track in Dynamics 365 Marketing tools and run in Teams as a streaming event with the Teams streaming setup integrated directly into the Dynamics 365 console.

In a sales example Taylor says, “We’re enabling sellers to be able to track the career movements of their contacts using the LinkedIn Sales Navigator, as well as connect very specific sales records within Microsoft Teams without ever having to leave Dynamics 365 Sales. So you can be in the Sales application and you have the ability to deeply understand a contact and any contact changes that occur in Teams, and that’s automatically updated in Sales.”

If your company is not an all-Microsoft shop and wants to use different tools as part of these workflows, Taylor says that you can use Microsoft cross-cloud connectors to connect to another service, and this is true regardless of the tasks involved (so long as the connector to the desired application is available).

Salesforce, a primary rival of Microsoft in the business software space, spent over $27 billion to buy Slack at the end of last year to bring this kind of integration to its platform. Taylor sees the acquisition as a reaction to the integration Microsoft already has and continues to build.

“I think that Salesforce had to acquire Slack to be able to have that collaboration [we have], so we are years ahead of what they’re going to be able to provide because they will not have these native integrations. So I actually see the Salesforce acquisition as a response to what we’re doing with Dynamics 365 and Teams,” Taylor told me.

It’s worth pointing out that Salesforce is far ahead of Microsoft when it comes market share in the CRM space with over 19% versus under 3% for Microsoft, according to Gartner numbers from 2019. While it’s possible these numbers have shifted some since then, probably not significantly.

Early Stage is the premiere ‘how-to’ event for startup entrepreneurs and investors. You’ll hear firsthand how some of the most successful founders and VCs build their businesses, raise money and manage their portfolios. We’ll cover every aspect of company-building: Fundraising, recruiting, sales, legal, PR, marketing and brand building. Each session also has audience participation built-in — there’s ample time included in each for audience questions and discussion.

Project management service Wrike today announced at its user conference a major update to its platform that includes a lot of new AI smarts for keeping individual projects on track and on time, as well as new solutions for marketers and project management offices in large corporations. In addition, the company also launched a new budgeting feature and tweaks to the overall user experience.

The highlight of the launch, though, is, without doubt, the launch of the new AI and machine learning capabilities in Wrike . With more than 20,000 customers and over 2 million users on the platform, Wrike has collected a trove of data about projects that it can use to power these machine learning models.

Image Credits: Wrike

The way Wrike is now using AI falls into three categories: project risk prediction, task prioritization and tools for speeding up the overall project management workflow.

Figuring out the status of a project and knowing where delays could impact the overall project is often half the job. Wrike can now predict potential delays and alert project and team leaders when it sees events that signal potential issues. To do this, it uses basic information like start and end dates, but more importantly, it looks at the prior outcomes of similar projects to assess risks. Those predictions can then be fed into Wrike’s automation engine to trigger actions that could mitigate the risk to the project.

Task prioritization does what you would expect and helps you figure out what you should focus on right now to help a project move forward. No surprises there.

What is maybe more surprising is that the team is also launching voice commands (through Siri on iOS) and Gmail-like smart replies (in English for iOS and Android). Those aren’t exactly core features of a project management tool, but as the company notes, these features help remove the overall friction and reduce latencies. Another new feature that falls into this category is support for optical character recognition to allow you to scan printed and handwritten notes from your phones and attach them to tasks (iOS only).

“With more employees working from home, work and personal life are becoming intertwined,” the company argues. “As workers use AI in their personal lives, team managers and everyday users expect the smarts they’re accustomed to in consumer devices and apps to help them manage their work as well. Wrike Work Intelligence is the most comprehensive machine learning foundation that taps into tens of millions of work-related user engagements to power cross-functional collaboration to help organizations achieve operational efficiency, create new opportunities and accelerate digital transformation. Teams can focus on the work that matters most, predict and minimize delays, and cut communication latencies.”

Image Credits: Wrike

The other major new feature — at least if you’re in digital marketing — is Wrike’s new ability to pull in data about your campaigns from about 50 advertising, marketing automation and social media tools, which is then displayed inside the Wrike experience. In a fast-moving field, having all that data at your fingertips and right inside the tool where you think about how to manage these projects seems like a smart idea.

Image Credits: Wrike

Somewhat related, Wrike’s new budgeting feature also now makes it easier for teams to keep their projects within budget, using a new built-in rate card to manage project pricing and update their financials.

“We use Wrike for an extensive project management and performance metrics system,” said Shannon Buerk, the CEO of engage2learn, which tested this new budgeting tool. “We have tried other PM systems and have found Wrike to be the best of all worlds: easy to use for everyone and savvy enough to provide valuable reporting to inform our work. Converting all inefficiencies into productive time that moves your mission forward is one of the keys to a culture of engagement and ownership within an organization, even remotely. Wrike has helped us get there.”

The “Sent via Superhuman iOS” email signature has become one of the strangest flexes in the tech industry, but its influence is enduring, as the $30 per month invite-only email app continues to shape how a wave of personal productivity startups are building their business and product strategies.

I had a chance to chat with Superhuman CEO and founder Rahul Vohra earlier this month during an oddly busy time for him. He had just announced a dedicated $7 million angel fund with his friend Todd Goldberg (which I wrote up here) and we also noted that LinkedIn is killing off Sales Navigator, a feature driven by Rapportive, which Vohra founded and later sold in 2012. All the while, his buzzy email company is plugging along, amassing more interested users. Vohra tells me there are now more than 275,000 people on the waitlist for Superhuman.

Below is a chunk of my conversation with Vohra, which has been edited for length and clarity.

TechCrunch: When you go out to raise funding and a chunk of your theoretical user base is sitting on a waitlist, is it a little tougher to determine the total market for your product?

Rahul Vohra: That’s a good question. When we were doing our Series B, it was very easily answered because we’re one of a cohort of companies, that includes Notion and Airtable and Figma, where the addressable market — assuming you can build a product that’s good enough — is utterly enormous.

With my last company, Rapportive, there was a lot of conversation around, “oh, what’s the business model? What’s the market? How many people need this?” This almost never came up in any fundraising conversation. People were more like, “well, if this thing works, obviously the market is basically all of prosumer productivity and that is, no matter how you define it, absolutely huge.”

The “Sent via Superhuman iOS” email signature has become one of the strangest flexes in the tech industry, but its influence is enduring, as the $30 per month invite-only email app continues to shape how a wave of personal productivity startups are building their business and product strategies.

I had a chance to chat with Superhuman CEO and founder Rahul Vohra earlier this month during an oddly busy time for him. He had just announced a dedicated $7 million angel fund with his friend Todd Goldberg (which I wrote up here) and we also noted that LinkedIn is killing off Sales Navigator, a feature driven by Rapportive, which Vohra founded and later sold in 2012. All the while, his buzzy email company is plugging along, amassing more interested users. Vohra tells me there are now more than 275,000 people on the waitlist for Superhuman.

Below is a chunk of my conversation with Vohra, which has been edited for length and clarity.

TechCrunch: When you go out to raise funding and a chunk of your theoretical user base is sitting on a waitlist, is it a little tougher to determine the total market for your product?

Rahul Vohra: That’s a good question. When we were doing our Series B, it was very easily answered because we’re one of a cohort of companies, that includes Notion and Airtable and Figma, where the addressable market — assuming you can build a product that’s good enough — is utterly enormous.

With my last company, Rapportive, there was a lot of conversation around, “oh, what’s the business model? What’s the market? How many people need this?” This almost never came up in any fundraising conversation. People were more like, “well, if this thing works, obviously the market is basically all of prosumer productivity and that is, no matter how you define it, absolutely huge.”